Book Changelog

This Machine Learning Systems textbook is constantly evolving. This changelog is intended to record all updates and improvements, helping you stay informed about what’s new and refined.

Automated Changelog

These changelog entries are automatically generated from our development process and should be mostly accurate. They track code changes, content updates, and improvements across the entire book. While the entries are comprehensive, they may occasionally contain minor inaccuracies or overly technical details.

2025 Updates

📅 June 10 at 05:13 PM

📄 Frontmatter

About: The About page now includes updated links to SocratiQ pages for improved navigation and user experience.

Let me know if you’d like me to elaborate on any specific changes within the commit messages! - SocratiQ: This update improves the SocratiQ page with updated internal links for better navigation. Additionally, it introduces documentation for the SocratiQ AI learning companion, providing users with more information about this helpful tool. - SocratiQ: The SocratiQ AI feature has been removed from SocratiQ. Additionally, several minor grammatical and content errors were corrected.

📖 Chapters

Chapter 1: Introduction: Chapter 1: Introduction was updated to include missing footnotes, correct minor grammatical errors, and refine the language for improved clarity and precision. These changes enhance the readability and accuracy of the introductory material.
Chapter 2: ML Systems: Chapter 2 on ML Systems has been enhanced with resource sections, refined language for improved clarity, and the addition of figures to enhance understanding. Minor grammatical errors and outdated content have also been addressed.

Let me know if you need further assistance! - Chapter 3: DL Primer: Chapter 3, “DL Primer,” was significantly updated with new resource sections, refined content for clarity and consistency, and added figures to enhance understanding. Corrections were made to grammar, content, and style definitions for improved accuracy. - Chapter 4: DNN Architectures: This update focuses on refining explanations of deep learning architectures, particularly CNNs, and enhancing the content with illustrative figures and data movement patterns. Minor typographical errors and formatting inconsistencies were also addressed for improved clarity. - Chapter 5: AI Workflow: Chapter 5’s AI Workflow content was enhanced by adding dedicated resource sections, refining text processing within QMD files for better accuracy, and improving overall clarity and consistency with added figures. - Chapter 6: Data Engineering: Chapter 6 on Data Engineering was updated with new resource sections, improved text processing, and several revisions to the content. Key changes include replacing Mermaid diagrams with TikZ for better rendering and adding a data pipeline overview diagram. - Chapter 7: AI Frameworks: Chapter 7 was updated with new resource sections and improvements to text processing, grammar, and figure references. Additional figures were also added to enhance the content. - Chapter 8: AI Training: Chapter 8 on AI Training has been significantly improved with the addition of resource sections, enhanced text processing for QMD files, and clearer explanations about activation checkpointing. Visuals have also been added to enhance understanding of the training process. - Chapter 9: Efficient AI: Chapter 9 on Efficient AI was updated with improved text processing, clearer explanations of scaling frontiers and efficiency dimensions, refined language in the scaling laws section, and corrected typos and diagram issues. Additional resources were also added to enhance the learning experience. - Chapter 10: Model Optimizations: Chapter 10 on Model Optimizations was significantly enhanced with clarifications on pruning strategies, additions of resource sections and new figures, along with refinements to documentation and corrections for grammatical errors and typos. The chapter now provides a more comprehensive and accurate overview of model optimization techniques. - Chapter 11: AI Acceleration: Chapter 11 on AI Acceleration was significantly improved with added resource sections, footnotes, and clarified definitions related to placement and allocation. The chapter also benefits from refined explanations, corrected code blocks, and new figures for better understanding of AI accelerator concepts. - Chapter 12: Benchmarking AI: This update enhances Chapter 12 on Benchmarking AI by adding resource sections, refining text processing for QMD files, correcting a typo, and improving the overall clarity and consistency of the content. These changes contribute to a more comprehensive and user-friendly learning experience. - Chapter 13: ML Operations: Chapter 13 on ML Operations was significantly updated to improve clarity and accuracy. This includes revisions to content, diagrams, figures, and footnotes for a more polished and informative chapter. - Chapter 14: On-Device Learning: Chapter 14 on On-Device Learning was updated with clearer explanations, refined concepts, and consistent formatting. Additionally, resource sections were added to the core content and table references were updated for improved clarity. - Chapter 18: Robust AI: Chapter 18 on Robust AI has been updated with clearer explanations, refined text, and improved formatting. This includes added resource sections, whitespace improvements, and a new figure environment for error masking. - Chapter 15: Security & Privacy: Chapter 15 on Security & Privacy was significantly expanded and refined, covering topics like threat mitigation strategies, adversarial attacks, trustworthy ML systems, and secure model design. The chapter now provides a comprehensive overview of privacy and security concepts relevant to machine learning. - Chapter 16: Responsible AI: Chapter 16 on Responsible AI was significantly enhanced with expanded discussions on core principles, deployment contexts, safety, robustness, privacy, fairness, and explainability. The chapter now includes practical applications of these principles, updated resources, and a clearer definition of Responsible AI. - Chapter 17: Sustainable AI: Chapter 17 on Sustainable AI was enhanced with added resource sections, and underwent revisions to improve grammar, content clarity, and text processing within QMD files. - Chapter 19: AI for Good: Chapter 19, “AI for Good,” was significantly updated with improvements to its content. This includes refining text for clarity and adding resource sections to enhance the learning experience.

🧑‍💻 Labs

Hands-on Labs: Updated content with 0 changes
Arduino: Updated content with 0 changes
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Grove Vision: Updated content with 0 changes

📅 May 14 at 08:29 PM

📖 Chapters

Chapter 14: On-Device Learning: The “On-Device Learning” chapter (contents/core/on-device_learning/ondevice_learning.qmd) has been updated with refactorings and clarifications to improve its content and readability.

📅 May 04 at 11:23 PM

📖 Chapters

Chapter 1: Introduction: The introduction chapter has been updated with content revisions to enhance clarity and improve the overall flow.
Chapter 2: ML Systems: Chapter 2 on ML Systems was updated with improvements to formatting and grammar in footnotes, specifically related to wake-word detection and privacy regulations. A script was also added to identify any missing references within the chapter content.
Chapter 3: DL Primer: The Chapter 3 DL Primer was updated to swap the dimension order of W^L for accuracy and include a script to identify any missing references. These changes ensure the content is both mathematically correct and comprehensively sourced.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 4: DNN Architectures: This update focuses on improving the accuracy and completeness of Chapter 4: DNN Architectures. It includes a script to identify and resolve any missing references within the chapter’s content.

Let me know if you’d like a more detailed summary or have other questions about these commit messages! - Chapter 5: AI Workflow: Please provide me with the actual commit messages for Chapter 5: AI Workflow (contents/core/workflow/workflow.qmd). I need the content of the messages to generate a summary of the updates. 😊

Once you give me the commit messages, I can help you create a concise summary highlighting the most important changes and improvements. - Chapter 6: Data Engineering: Please provide me with the commit messages for Chapter 6: Data Engineering (contents/core/data_engineering/data_engineering.qmd). I need the actual commit message text to generate a summary of the changes.

Once you give me the commit messages, I can analyze them and provide a concise summary of the key updates. - Chapter 7: AI Frameworks: The Chapter 7: AI Frameworks section was updated to include content from Chapter 6. This update likely involves integrating information about various AI frameworks into the existing framework content.

Let me know if you’d like me to analyze more specific commits or provide a summary based on additional context! - Chapter 8: AI Training: Chapter 8: AI Training has been refined with fixes for minor issues and enhancements to the label checking system. These changes improve the accuracy and clarity of the training content. - Chapter 9: Efficient AI: Chapter 9, “Efficient AI,” was updated with fixes from Bravo to improve its content accuracy and clarity. These changes enhance the understanding of efficient AI concepts within the chapter. - Chapter 10: Model Optimizations: Please provide the content of the Git commit messages for Chapter 10: Model Optimizations so I can generate a summary of the updates. I need the actual text of the commit messages to understand what changes were made.

Let me know if you have any other questions! - Chapter 11: AI Acceleration: Chapter 11 on AI Acceleration was refined to improve clarity and accuracy. This includes enhancements to the explanations of hardware specialization, AI compute primitives, and overall hardware acceleration concepts. - Chapter 12: Benchmarking AI: Chapter 12’s content on AI Benchmarking has been improved with clearer explanations of benchmarking metrics and power measurements. Additionally, a script was added to ensure all references are present. - Chapter 13: ML Operations: Chapter 13 on MLOps was expanded with new core concepts and case studies. Stylistic improvements were made, including consolidating TikZ figure styling and fixing acronyms, along with addressing missing references within the chapter. - Chapter 14: On-Device Learning: The Chapter 14 on On-Device Learning was significantly updated with a focus on clarity and comprehensiveness. Key additions include definitions, design guidance, security concerns, privacy explanations, adaptation strategies, and a conclusion with challenges and limitations. - Chapter 18: Robust AI: This update focuses on refining Chapter 18, “Robust AI”. It includes fixes for minor issues, improved label checking, added a script to identify missing references, and resolved issues with package, Helvetica font, and line commands. - Chapter 15: Security & Privacy: This update addresses minor issues within Chapter 15 and enhances the accuracy of label checking for improved clarity and consistency. - Chapter 17: Sustainable AI: This update focuses on visual consistency and accuracy in Chapter 17. It standardizes TikZ figure styling for a more cohesive look and includes a script to identify any missing references, ensuring completeness and reliability of the content. - Chapter 19: AI for Good: This update to Chapter 19 focuses on improving accuracy and completeness. It corrects a footnote about PlantVillage Nuru and includes a script to identify any missing references for better sourcing.

🧑‍💻 Labs

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Shared: Updated content with 0 changes

📅 March 25 at 11:51 PM

📄 Frontmatter

Foreword: Style and formatting were improved in the foreword based on feedback from Vale testing.

Let me know if you’d like me to elaborate on any specific changes! - About: Vale testing identified and addressed several issues in the About page’s markdown content. These updates ensure consistent formatting and adherence to style guidelines. - Acknowledgements: The contributor list in the acknowledgements file has been updated.

This update ensures that all individuals who have contributed to the project are properly recognized. - SocratiQ: This update fixes all broken links in the SocratiQ documentation and removes trailing whitespace for cleaner code.

Let me know if you have any other commit messages you’d like summarized!

📖 Chapters

Chapter 1: Introduction: This update to Chapter 1 focuses on cleaning up Markdown styles and formatting, including making footnote naming consistent and removing unused code. It also addresses build errors and refines the content with revisions to section headers and sentence completion.
Chapter 2: ML Systems: Chapter 2, “ML Systems,” has been updated with improved formatting, including consistent footnote styles and corrected hyphenation. The update also fixes typos, ensures proper reference linking, and streamlines section headers for clarity.
Chapter 3: DL Primer: This update focused on refining the style and content of Chapter 3: DL Primer. It includes updated footnote formatting, clearer definitions, and revisions to section headers for improved readability.
Chapter 4: DNN Architectures: Chapter 4 on DNN Architectures was updated with several style and formatting improvements. This includes fixing hyphenation, standardizing colon usage, resolving broken links, and ensuring all figure references are present.
Chapter 5: AI Workflow: This update refines Chapter 5 on AI Workflow, focusing on style consistency and content improvements. Key changes include adding definitions, updating references, and implementing initial content revisions for a clearer understanding of the workflow.
Chapter 6: Data Engineering: This update for Chapter 6: Data Engineering focuses on stylistic improvements, including consistent formatting and Markdown style changes. It also addresses several technical issues like broken links and incorrect figure references.
Chapter 7: AI Frameworks: Chapter 7: AI Frameworks was updated with a new figure for ONNX, consistent footnote naming, and corrected callout and link formatting. These changes improve the visual clarity and accuracy of the chapter content.
Chapter 8: AI Training: Chapter 8 on AI Training was updated with content revisions, including manual merges from separate branches for sidenotes and development features. The update also involved stylistic improvements to markdown formatting and ensuring consistent footnote naming conventions.
Chapter 9: Efficient AI: Chapter 9 on Efficient AI was significantly updated with a new section on Scaling Laws, additional content about scaling regimes, and improvements to the existing structure and text. Various stylistic and formatting changes were also made throughout the chapter.
Chapter 10: Model Optimizations: Chapter 10’s content on model optimizations was refined with fixes to spelling, style inconsistencies, and broken links. The update also includes improved clarity through added footnotes and consistent referencing of figures and tables.
Chapter 11: AI Acceleration: This update to Chapter 11 focuses on refining style and consistency. It includes fixes for spelling, acronym usage, table and figure referencing, footnote naming, and caption information.
Chapter 12: Benchmarking AI: Chapter 12 on Benchmarking AI has been updated with several improvements. This includes fixing broken links, reviewing and adjusting section headers, adding a missing figure reference, and cleaning up Markdown styles for better readability.
Chapter 13: ML Operations: This update focuses on refining Chapter 13’s content on ML Operations. Key improvements include restructuring core components, enhancing the narrative flow, updating case studies, and correcting stylistic inconsistencies and broken links for clarity and accuracy.
Chapter 14: On-Device Learning: This update addresses styling inconsistencies and fixes all broken links within Chapter 14 on On-Device Learning. It also includes an initial review of the chapter content.
Chapter 18: Robust AI: Chapter 18 on Robust AI was significantly updated with new content on poisoning attacks, transient and permanent faults, and real-world applications. The chapter also received improvements to its structure, clarity, and style, including updated learning objectives, a revised conclusion, and corrected links.
Chapter 15: Security & Privacy: This update to Chapter 15 focuses on improving readability and accuracy. It fixes all broken links and cleans up Markdown styles for better formatting.
Chapter 16: Responsible AI: Chapter 16 on Responsible AI has been updated with improved Markdown styling and all broken links have been fixed. This initial update lays the foundation for further content development on this important topic.
Chapter 17: Sustainable AI: Chapter 17, “Sustainable AI,” was significantly updated with content about Jevon’s Paradox, including a plot visualization. The chapter also received general improvements such as spelling corrections, formatting adjustments, and enhanced readability.
Chapter 19: AI for Good: Chapter 19, “AI for Good,” received significant updates including consistent styling and formatting, improved footnotes, and the correction of all broken links. These changes enhance the readability and accuracy of the chapter content.
Chapter 20: Conclusion: This update focused on cleaning up Chapter 20 by removing any unnecessary or dangling sections, improving the overall structure and clarity of the conclusion.

Let me know if you’d like me to elaborate on specific commits! - Chapter: Generative Ai: The initial version of the “Generative AI” chapter was created, outlining core concepts and laying the foundation for further development. This first pass provides a basic framework for understanding generative AI within the broader context of the project.

Let me know if you have any other commit messages you’d like summarized! - Chapter: Old Sus Ai: This chapter has been updated by removing an old file and implementing various improvements. The focus is on enhancing the content within “old_sus_ai.qmd” for better clarity and accuracy.

Let me know if you’d like me to elaborate on any specific aspect of the changes!

🧑‍💻 Labs

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Raspberry Pi: Updated content with 0 changes

📚 Appendix

PhD Survival Guide: This update addresses two key issues: it fixes several spelling errors identified by the codespell check and repairs all broken links within the PhD Survival Guide.

📅 March 03 at 10:31 PM

📄 Frontmatter

About: The “About” page’s commit history focused primarily on improving formatting and consistency with linting for header spacing. This ensures a cleaner and more visually appealing presentation of information.

Let me know if you have any other Git messages you’d like summarized! - Acknowledgements: The contributor list was updated in both the README and acknowledgements.qmd file. This ensures all contributors are properly acknowledged for their work.

Let me know if you have any other Git commit messages you’d like summarized! - SocratiQ: This update addresses several minor issues related to code style and formatting within SocratiQ’s documentation. Specifically, it fixes callout titles, resolves linting errors in QMD files, and ensures consistent header spacing.

📖 Chapters

Chapter 1: Introduction: This update addresses formatting issues in Chapter 1’s introduction, specifically fixing callout titles and inconsistencies in separators. It also resolves problems with linting QMD files to ensure code quality.

Let me know if you have any other text you’d like summarized! - Chapter 2: ML Systems: This update resolves formatting inconsistencies and addresses lint errors within the Chapter 2: ML Systems content. The changes ensure proper Markdown formatting and adherence to coding style guidelines for the QMD files.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 3: DL Primer: The “DL Primer” chapter in Chapter 3 received several updates, including fixes to callout title formatting and whitespace issues, as well as improvements to linting and header spacing for better code readability and consistency.

Let me know if you’d like a more detailed breakdown of any specific changes! - Chapter 4: DNN Architectures: Chapter 4 on DNN Architectures was updated with fixes to callout titles, linting issues in QMD files, and content revisions within the dnn_architectures.qmd file. These changes improve formatting consistency and address potential errors within the chapter’s Markdown structure. - Chapter 5: AI Workflow: The Chapter 5 content on AI Workflow was refined with several improvements. This includes removing redundancies, correcting text errors, and ensuring proper code formatting through linting fixes. - Chapter 6: Data Engineering: This commit batch addresses various formatting and technical issues in Chapter 6’s Data Engineering content. Fixes include resolving build errors, improving callout titles, and standardizing formatting throughout the chapter using QMD linting. - Chapter 7: AI Frameworks: Chapter 7 on AI Frameworks was updated with improvements to clarity and formatting, including the addition of images illustrating model and data parallelism for distributed execution. Redundant definitions were also removed, streamlining the chapter’s content. - Chapter 8: AI Training: Chapter 8 on AI Training was updated to include descriptions of single and multi-GPU systems, along with improvements to formatting, definitions, and linting. Redundant definitions were removed and script help was integrated for clarity. - Chapter 9: Efficient AI: This update to Chapter 9 on Efficient AI focuses on improving clarity and conciseness. Redundant definitions were removed, spacing and formatting issues were fixed, and linting errors were addressed for a cleaner and more readable chapter. - Chapter 10: Model Optimizations: Chapter 10 was significantly updated to include a comprehensive section on model optimization techniques, covering topics like quantization, pruning, and calibration. The chapter also received numerous improvements in formatting, figures, references, and clarity. - Chapter 11: AI Acceleration: Chapter 11 on AI acceleration was significantly updated, including content on host accelerators, multi-GPU setups, and various mapping strategies. The chapter also features improvements to figures, formatting, and references. - Chapter 12: Benchmarking AI: Chapter 12 was updated to improve visual consistency by replacing PNGs with TikZ code and adding an image for datacentric AI. Several other changes were made, including fixing references, improving formatting, removing redundancies, and addressing linting issues. - Chapter 13: ML Operations: This update to Chapter 13 focuses on code quality and clarity. It removes redundant definitions, corrects formatting issues in callouts, and implements necessary linting fixes for the QMD files. - Chapter 14: On-Device Learning: This update focuses on cleaning up and improving the readability of Chapter 14 content. It includes fixing typos, removing redundant definitions, correcting callout formatting, and resolving linting issues in the QMD files. - Chapter 18: Robust AI: This update focuses on cleaning up formatting and code within Chapter 18, addressing redundant definitions, callout title issues, and overall style inconsistencies. It also incorporates linting fixes to ensure code quality and consistency. - Chapter 15: Security & Privacy: This update for Chapter 15 focuses on improving formatting and clarity. Redundant definitions were removed, callout titles were standardized, and various formatting issues were addressed to enhance readability. - Chapter 16: Responsible AI: This update focuses on improving the formatting and structure of Chapter 16’s content. It includes fixes for callout titles and resolves issues with linting, ensuring the chapter adheres to coding standards and presents information clearly. - Chapter 17: Sustainable AI: This update focuses on improving clarity and consistency in Chapter 17. Redundant definitions were removed, callout titles were formatted correctly, and issues with QMD file linting were resolved. - Chapter 19: AI for Good: This update to Chapter 19 primarily focuses on improving code and style consistency. Redundant definitions were removed, callout titles were formatted correctly, and linting issues were addressed for better readability and maintainability.

Let me know if you’d like me to elaborate on any specific commit message!

🧑‍💻 Labs

Hands-on Labs: Updated content with 0 changes
Arduino: Updated content with 0 changes
Raspberry Pi: Updated content with 0 changes

📅 February 08 at 12:29 AM

📄 Frontmatter

Acknowledgements: The commit updates both the README file and the acknowledgments file, adding contributions from various individuals. This ensures proper recognition for those who have contributed to the project.
SocratiQ: Please provide the Git commit messages for SocratiQ (contents/frontmatter/ai/socratiq.qmd) so I can generate a brief summary of the updates.

Once you give me the commit messages, I can analyze them and create a concise summary highlighting the most important changes and improvements.

📅 February 07 at 11:50 PM

📄 Frontmatter

Index: The precheck command now only runs on .qmd and .bib files, improving efficiency by excluding other file types. This change focuses the precheck process on core document components for more targeted validation.
About: The “precheck” script now specifically targets .qmd and .bib files, improving efficiency by excluding other file types. This change streamlines the build process and focuses resource allocation on essential content files.

Let me know if you’d like a more detailed summary or have any other questions about these commit messages! - Changelog: The changelog generation process was automated, removing manual updates and streamlining the process. This allows for more efficient and accurate documentation of changes.

Let me know if you’d like me to elaborate on any specific commit message! - Acknowledgements: Multiple commits updated the README and acknowledgments file to include a list of contributors. This update was made across several branches, reflecting ongoing development efforts. - SocratiQ: The precheck functionality in SocratiQ now focuses specifically on .qmd and .bib files, improving efficiency and streamlining the workflow. This change ensures that the precheck process targets relevant content for accurate analysis and error detection.

Let me know if you need any further assistance or have more commit messages to analyze!

📖 Chapters

Chapter 1: Introduction: Updates to Chapter 1 focused on streamlining dependencies by removing unused libraries and relying solely on the _quarto.yml configuration file. Additionally, the precheck functionality was refined to specifically target .qmd and .bib files for improved efficiency.
Chapter 2: ML Systems: The main update for Chapter 2: ML Systems focused on refining the content within the ml_systems.qmd file, ensuring accuracy and clarity. Additionally, the precheck functionality was improved to only process .qmd and .bib files, streamlining the workflow.
Chapter 3: DL Primer: The precheck function now specifically targets .qmd and .bib files, improving efficiency and focus. This change streamlines the workflow for content creation within Chapter 3.

Let me know if you’d like a more detailed summary or have any other questions about these changes! - Chapter 4: DNN Architectures: The precheck script now only runs on .qmd and .bib files, streamlining the process.

This focuses on the most significant change - improving efficiency by targeting specific file types for the precheck. - Chapter 5: AI Workflow: The precheck function now only runs on .qmd and .bib files, streamlining the workflow and improving efficiency. This change focuses the precheck process on relevant content for Chapter 5. - Chapter 6: Data Engineering: The precheck script now only runs on .qmd and .bib files, improving efficiency by excluding other file types. This change streamlines the process for data engineers focusing on content creation.

Let me know if you need help summarizing any other Git commit messages! - Chapter 7: AI Frameworks: This update streamlines Chapter 7 by removing unused libraries directly from the code and relying solely on _quarto.yml for dependencies. Additionally, the pre-check functionality is now restricted to .qmd and .bib files for improved efficiency. - Chapter 8: AI Training: This update focuses on improving the visual presentation and technical aspects of Chapter 8. It fixes figure formatting, updates a diagram, removes unnecessary code dependencies, and streamlines the precheck process for .qmd and .bib files. - Chapter 9: Efficient AI: This update focuses on integrating R code into Chapter 9 for demonstrating and debugging efficient AI concepts. It also includes various fixes like addressing feedback, resolving bib references, and streamlining precheck functionality. - Chapter 10: Model Optimizations: The precheck process now specifically targets QMD and Bib files, streamlining the optimization workflow. This change improves efficiency by focusing checks on relevant file types.

Let me know if you’d like me to elaborate on any specific commit or aspect of the changes! - Chapter 11: AI Acceleration: The precheck functionality in Chapter 11 now exclusively targets .qmd and .bib files, streamlining the process for specific file types. This change improves efficiency by focusing the precheck on relevant content within the chapter. - Chapter 12: Benchmarking AI: Chapter 12, Benchmarking AI, was significantly updated with new visualizations showcasing power trends in MLPerf and FastML, motivated by the need for benchmarking. The chapter also received refinements to text flow, model updates based on feedback, and a focus on components of benchmark challenges. - Chapter 13: ML Operations: The precheck functionality is now restricted to running on .qmd and .bib files, streamlining the workflow for Chapter 13. This change ensures that the precheck process focuses specifically on the relevant content for this chapter.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 14: On-Device Learning: The precheck functionality now specifically targets .qmd and .bib files, improving efficiency by focusing on relevant content. This change streamlines the process for Chapter 14’s On-Device Learning content. - Chapter 18: Robust AI: The precheck now only runs on .qmd and .bib files, streamlining the process and improving efficiency. This change focuses on ensuring accurate checks for core content types within Chapter 18. - Chapter 15: Security & Privacy: The precheck process now only runs on .qmd and .bib files, improving efficiency for other file types within Chapter 15. This change streamlines the build process and focuses resources on essential content formats.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 16: Responsible AI: The precheck script now only runs on .qmd and .bib files, improving efficiency and focus. This change streamlines the development process for Chapter 16 by targeting specific file types crucial to its content. - Chapter 17: Sustainable AI: The precheck now only runs on .qmd and .bib files, improving efficiency for other file types within Chapter 17. This change streamlines the workflow by focusing the precheck on relevant content specifically.

Let me know if you’d like a summary of any other commits! - Chapter 19: AI for Good: Updates to Chapter 19, “AI for Good,” include using local libraries and caching PNGs instead of relying on potentially broken remote URLs. Additionally, the precheck functionality has been refined to target only QMD and Bib files. - Chapter 20: Conclusion: The precheck now specifically targets .qmd and .bib files, ensuring focused validation of content and citations within Chapter 20. This targeted approach streamlines the workflow and improves efficiency.

🧑‍💻 Labs

Hands-on Labs: Updated content with 0 changes
Arduino: Updated content with 0 changes
Seeed XIAO ESP32S3: Updated content with 0 changes
Raspberry Pi: Updated content with 0 changes
Shared: Updated content with 0 changes

📚 Appendix

PhD Survival Guide: The precheck now only runs on .qmd and .bib files, improving efficiency by focusing on relevant document types.

Let me know if you’d like me to elaborate on any specific commit message!

📅 February 02 at 11:14 PM

📄 Frontmatter

Acknowledgements: The commit history shows multiple updates to both the README and the acknowledgements.qmd file, primarily focused on adding contributors to these sections. This suggests ongoing efforts to maintain and update contributor lists within the project documentation.

📖 Chapters

Chapter 1: Introduction: The commit message indicates that all callout ###* titles in Chapter 1’s introduction were changed to a standard title block format for improved consistency and readability.
Chapter 2: ML Systems: The Chapter 2 “ML Systems” content has been updated to use title blocks for all callout sections, improving visual structure and readability. This change enhances the overall presentation and clarity of the chapter.
Chapter 3: DL Primer: The commit messages indicate that all callout titles within Chapter 3, “DL Primer,” have been updated to use a consistent title block format. This change likely improves the visual structure and readability of the chapter.
Chapter 4: DNN Architectures: This update fixes an erratum and standardizes the formatting of callout titles in Chapter 4 on DNN Architectures by changing them from ###* to a consistent title block format.
Chapter 5: AI Workflow: The commit messages indicate that the formatting of callouts in Chapter 5’s workflow documentation was updated to use title blocks instead of the previous ###* style. This change likely improves the visual consistency and readability of the chapter.

Let me know if you need further assistance summarizing these changes or any other Git commit messages! - Chapter 6: Data Engineering: The commit messages indicate that all callout titles within Chapter 6: Data Engineering were standardized using a title block format, improving the chapter’s visual consistency and structure.

This change likely enhances readability and organization for users navigating the content. - Chapter 7: AI Frameworks: The chapter now consistently uses the tikz package throughout for drawing diagrams, improving readability and consistency. This change also involves moving the usetikz declarations into a separate header file for better organization.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 8: AI Training: Chapter 8 on AI Training received minor updates including revisions to Figure 8.8, improved figure sizing, and the addition of diagrams for better visual understanding. Code within the chapter was also corrected for accuracy. - Chapter 9: Efficient AI: The “Efficient AI” chapter was updated to use a consistent title block format for callouts and had its bibliography revised for accuracy. This ensures a clearer and more professional presentation of information in the chapter. - Chapter 10: Model Optimizations: The commit updates all callout ###* titles in Chapter 10 to use the more structured “title block” format. This improves the visual consistency and readability of the chapter. - Chapter 11: AI Acceleration: The commit messages indicate that Chapter 11’s formatting was improved by updating callout titles from ###* to a standardized title block format. This change likely enhances readability and consistency within the chapter.

Let me know if you’d like me to elaborate on any specific aspect of these changes! - Chapter 12: Benchmarking AI: Chapter 12 on Benchmarking AI was significantly revised with improvements to the learning objectives, content organization, and figures. This includes updated references, corrected mathematical expressions, and the addition of a new case study. - Chapter 13: ML Operations: The commit messages indicate that all callout titles within Chapter 13 (“ML Operations”) of the “contents/core/ops/ops.qmd” file have been updated to use the title block format. This change likely improves the visual structure and readability of the chapter.

Let me know if you’d like me to elaborate on any specific aspect of these changes! - Chapter 14: On-Device Learning: The commit messages indicate that the formatting of callout titles in Chapter 14 was updated from “###*” to a consistent title block format. This likely improves readability and visual consistency within the chapter. - Chapter 18: Robust AI: The commit messages indicate that all callout titles in Chapter 18, “Robust AI,” were updated from ###* format to a more structured title block format. This likely improves the visual clarity and organization of the chapter content.

Let me know if you’d like me to elaborate on any specific aspect or commit message! - Chapter 15: Security & Privacy: The commit messages indicate that Chapter 15’s headings using ###* were changed to a standardized title block format for improved consistency and readability.

Let me know if you have any other Git commit messages you’d like summarized! - Chapter 16: Responsible AI: The commit updates Chapter 16 by replacing all “callout” titles with a more structured title block format, improving readability and organization within the chapter. This change enhances the visual presentation and clarity of the Responsible AI content. - Chapter 17: Sustainable AI: This update refactors Chapter 17’s callout headings by converting them from ###* to a standardized title block format, improving consistency and readability.

Let me know if you have any other commit messages you’d like summarized! - Chapter 19: AI for Good: The commit updates all callout titles within Chapter 19, “AI for Good,” from using the ###* format to a standard title block format. This change likely improves the chapter’s visual structure and consistency.

📅 January 28 at 12:20 PM

📄 Frontmatter

Acknowledgements: The acknowledgements section was updated to include a list of contributors. Additional changes include adding logos and updating the README file.

📖 Chapters

Chapter 1: Introduction: A redundant case study was removed from Chapter 1: Introduction to streamline the content and improve clarity. This update focuses on making the introduction more concise and impactful.
Chapter 2: ML Systems: This update focuses on improving the visual presentation of Chapter 2. Radar plots were added to enhance the clarity and understanding of ML system concepts.

Let me know if you’d like me to elaborate on any specific changes or generate a more detailed summary! - Chapter 4: DNN Architectures: Chapter 4 on DNN Architectures was updated with wording revisions and improvements based on feedback from Bravo. These changes aim to enhance clarity and accuracy within the chapter content. - Chapter 5: AI Workflow: Please provide me with the Git commit messages for Chapter 5: AI Workflow (contents/core/workflow/workflow.qmd). I need the actual message content to generate a summary.

Once you give me the commit messages, I can analyze them and provide a brief, informative summary of the key updates. - Chapter 6: Data Engineering: Chapter 6 received significant updates including revised formatting, removal of outdated exercise references and content, new data engineering content, and added citations for improved accuracy. The chapter also underwent edits to later sections and work in progress was made on keyword improvements. - Chapter 7: AI Frameworks: Chapter 7 now includes figures illustrating AI chips, along with minor text edits and additions to bibliographic references. - Chapter 8: AI Training: Chapter 8 on AI Training was significantly updated with new figures illustrating chip architectures, a revised Mermaid chart, and improvements to the training process explanation. Several technical issues, including LaTeX rendering and package conflicts, were also addressed for better clarity and accuracy. - Chapter 9: Efficient AI: Chapter 9 on Efficient AI was significantly improved with the addition of learning objectives, updated references, figures, and content discussing Moore’s Law. The chapter also received formatting tweaks for better readability and visual appeal. - Chapter 10: Model Optimizations: This update focuses on cleaning up Chapter 10 by removing unnecessary references within the “optimizations.qmd” file, improving code readability and organization.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 11: AI Acceleration: This commit focused on cleaning up Chapter 11 by removing outdated or irrelevant references within the “hw_acceleration” section of the document.

Let me know if you’d like me to elaborate on any specific changes mentioned in the commit messages! - Chapter 19: AI for Good: This update for Chapter 19 significantly enhances the “AI for Good” section with added videos, images, and text refinements. Major improvements include updated learning objectives, spotlight use cases, and additional references to strengthen the content.

🧑‍💻 Labs

Raspberry Pi: Updated content with 0 changes

📚 Appendix

PhD Survival Guide: The PhD Survival Guide appendix was updated with additional resources, including links to helpful websites and materials. The guide also received minor text edits for improved clarity and accuracy.

📅 January 17 at 07:05 AM

📄 Frontmatter

About: Please provide the Git commit messages so I can generate a summary of the updates to the About section.
Acknowledgements: The commit history shows repeated updates to both the README and acknowledgements.qmd files, consistently adding new contributors to the project. This indicates a focus on recognizing and acknowledging the contributions of individuals to the project’s development.
SocratiQ: Please provide the actual commit messages so I can summarize the changes made to SocratiQ.

📖 Chapters

Chapter 1: Introduction: This commit incorporates feedback from Bravo, refining the content and clarity of Chapter 1: Introduction in the QMD file. The changes focus on improving the overall quality and effectiveness of the introductory chapter.
Chapter 2: ML Systems: This update merges the “dev” branch into the main branch, addressing issues introduced by a previous merge and improving PDF rendering within Chapter 2.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 3: DL Primer: Please provide the commit messages so I can generate a summary for you. I need the actual text of the commit messages to understand what changes were made to Chapter 3: DL Primer.

Once you give me the commit messages, I can help you create a concise and informative summary. - Chapter 4: DNN Architectures: This update clarifies how parameters are stored for Recurrent Neural Networks (RNNs), addressing issue #612. The commit also improves the table format using reStructuredText and footnotes for better readability. - Chapter 6: Data Engineering: This commit implements feedback from Bravo regarding Chapter 6: Data Engineering. Specific content edits were made to improve clarity and accuracy within the chapter.

Let me know if you have other Git commit messages you’d like summarized! - Chapter 7: AI Frameworks: Chapter 7 on AI Frameworks was significantly updated with a new framework overview, historical context, computational graph section, and improved clarity through wording tweaks and copyediting. Visual elements like timeline plots and graphs were also added to enhance understanding. - Chapter 12: Benchmarking AI: The primary change in Chapter 12 is a fix for a reference issue within the benchmarking section. This ensures accuracy and clarity in the content.

Let me know if you’d like me to elaborate on any specific commit message!

🧑‍💻 Labs

Raspberry Pi: Updated content with 0 changes

📅 January 12 at 03:40 PM

📄 Frontmatter

Acknowledgements: The commit messages indicate that the “readme” and “acknowledgements.qmd” files were updated multiple times to include a list of contributors. This suggests an effort to recognize and credit individuals who contributed to the project.

Let me know if you’d like me to analyze any other Git commit messages!

📖 Chapters

Chapter 1: Introduction: This update addresses issues introduced by PDF rendering improvements, including fixing a formatting issue with triple backticks and resolving merge conflicts. The changes also include minor tweaks to section headers for improved readability.
Chapter 2: ML Systems: This update to Chapter 2 on ML Systems focuses on clarifying key concepts. It includes definitions for hybrid ML and introduces a decision playbook framework, along with updated definitions for various sections within the chapter.
Chapter 5: AI Workflow: The main updates for Chapter 5: AI Workflow focus on improving PDF rendering within the workflow. This includes addressing bugs and implementing Zishen’s fixes.

Let me know if you have any other text you’d like summarized! - Chapter 6: Data Engineering: This update addresses formatting and content issues in Chapter 6. It includes fixes to figure sizing, data labeling sections, and incorporates contributions from Zishen and Bravo.

📅 January 11 at 04:51 PM

📄 Frontmatter

About: The “About” section was updated with various edits to the contents/frontmatter/about/about.qmd file.

Let me know if you’d like me to elaborate on any specific changes mentioned in the commit message! - Acknowledgements: The acknowledgements.qmd file was updated to include a list of contributors. This update recognizes the individuals who have contributed to the project. - SocratiQ: Please provide me with the content of the Git commit messages for contents/frontmatter/ai/socratiq.qmd. I need the actual text of the messages to generate a summary of the changes.

Once you give me the commit messages, I can analyze them and provide a brief, informative summary of the key updates.

📖 Chapters

Chapter 1: Introduction: This update incorporates changes from the upstream ‘dev’ branch and focuses on improving PDF rendering within Chapter 1. It also includes the addition of footnotes to enhance readability and clarity.
Chapter 2: ML Systems: This update to Chapter 2 on ML Systems introduces a decision playbook framework to guide users and clarifies key definitions within each section. It also incorporates a tectonic analogy for better understanding complex system interactions.
Chapter 5: AI Workflow: This commit removes a redundant fix request from a previous commit. The core focus remains on clarifying and improving the AI workflow documentation within Chapter 5.

Let me know if you’d like me to elaborate on any specific aspect of the commits! - Chapter 6: Data Engineering: This chapter saw several improvements, including fixes to build issues, updates to web scraping content and synthetic data generation methods, and refinements to the problem definition and overall overview.

📅 January 09 at 11:49 AM

📄 Frontmatter

Acknowledgements: The readme and acknowledgements.qmd files were updated to include a list of contributors.

This ensures proper credit is given to those who helped develop this project.

📖 Chapters

Chapter 1: Introduction: The introduction chapter received updates based on Marco’s feedback, focusing on improving clarity and content. These changes likely enhance the overall readability and understanding of the introductory material for Chapter 1.

Let me know if you’d like me to analyze more specific commit messages! 😊 - Chapter 5: AI Workflow: This update addresses feedback received for Chapter 5: AI Workflow by refining its content and ensuring clarity.

Let me know if you’d like me to elaborate on any specific changes mentioned in the commit messages! - Chapter 6: Data Engineering: This commit removes unnecessary fix requests related to grammar from previous revisions. The focus now shifts solely to content and structure within Chapter 6 on Data Engineering. - Chapter 7: AI Frameworks: This update removes unnecessary fix requests related to grammar in the Chapter 7 “AI Frameworks” section. The focus is now solely on content accuracy and clarity. - Chapter 8: AI Training: This update addresses feedback received on Chapter 8: AI Training by refining its content for clarity and accuracy.

Let me know if you’d like me to elaborate on specific changes mentioned in the commit messages! - Chapter 11: AI Acceleration: This commit addresses feedback from Bravo regarding Chapter 11 on AI Acceleration. The changes likely involve refining content and improving clarity within the chapter.

Let me know if you have any other Git commit messages you’d like summarized! - Chapter 16: Responsible AI: Updates to Chapter 16 “Responsible AI” address feedback received from Bravo, ensuring clarity and accuracy in the content.

Let me know if you’d like me to elaborate on any specific changes within the commit messages!

📅 January 07 at 10:19 AM

📄 Frontmatter

Foreword: The foreword content has been refined with minor wording adjustments to improve clarity and readability.
Acknowledgements: The acknowledgements.qmd file was updated to include a list of contributors.

This update recognizes the individuals who contributed to the project.

📖 Chapters

Chapter 1: Introduction: This update clarifies the difference between artificial intelligence (AI) and machine learning (ML), providing readers with a better understanding of these fundamental concepts.
Chapter 3: DL Primer: Chapter 3’s “DL Primer” was enhanced with added images and code to better explain the training loop and inference process. Specific improvements include code snapshots for both training (version 3.5) and inference (version 3.6), along with a correction for a typographical error.
Chapter 4: DNN Architectures: Chapter 4: DNN Architectures has been updated with new images based on feedback, enhancing visual clarity. Additionally, visualizations and interactive tools have been added to further illustrate DNN architectures.

📅 January 03 at 04:44 PM

📄 Frontmatter

Acknowledgements: This commit updates both the README and the acknowledgments file to include a list of contributors.
SocratiQ: Please provide the Git commit messages so I can generate a summary of the SocratiQ updates.

📖 Chapters

Chapter 1: Introduction: Please provide the Git commit messages for Chapter 1: Introduction (contents/core/introduction/introduction.qmd). I need the commit messages to generate a summary of the updates.
Chapter 2: ML Systems: Please provide the Git commit messages for Chapter 2: ML Systems so I can generate a summary of the updates.
Chapter 4: DNN Architectures: This update addresses several fixes within the Chapter 4 content on DNN Architectures. The primary focus is ensuring accuracy and clarity in describing various DNN architectures.

Let me know if you’d like me to elaborate on specific commits or areas of improvement! - Chapter 6: Data Engineering: Please provide the Git commit messages so I can generate a summary of the updates to Chapter 6: Data Engineering. - Chapter 20: Conclusion: This update addresses various fixes within Chapter 20: Conclusion to ensure accuracy and clarity. The core content of the conclusion remains unchanged, but minor revisions have been made to improve readability and address any potential issues.

Let me know if you’d like a more detailed summary of specific changes!

📅 January 02 at 09:06 PM

📄 Frontmatter

Acknowledgements: The acknowledgements.qmd file was updated to include a list of contributors. This update ensures proper credit is given to those who contributed to the project.

📖 Chapters

Chapter 4: DNN Architectures: This update cleans up Chapter 4 on DNN Architectures by removing dead commented text and incorporating Bravo’s suggested fixes for clarity and accuracy. The changes focus on improving the readability and quality of the content.
Chapter 20: Conclusion: Chapter 20’s conclusion received feedback and revisions from (Bravo?), addressing unspecified issues for improved clarity and accuracy.
Chapter: Generative Ai: This commit cleans up the “Generative Ai” chapter by removing outdated and commented-out text, improving readability and clarity.

📅 January 01 at 11:42 PM

📄 Frontmatter

Index: The abstract of the index document was updated for clarity and accuracy. This ensures the introductory information about the project is well-represented.

Let me know if you’d like me to elaborate on any specific changes within the abstract! - Foreword: The foreword was revised to improve the flow and clarity of its content. Several edits addressed formatting issues, typos, and reorganized sections for better readability. - About: The About page content was reorganized to improve flow and clarity, addressing feedback from Bravo and updating the chapter order for better readability. - Acknowledgements: The acknowledgements section was updated to include a list of contributors. This update ensures proper recognition of individuals who contributed to the project.

Let me know if you’d like me to elaborate on any specific details from the commit messages! - SocratiQ: This update to SocratiQ focused on web formatting improvements and organizational restructuring within the content.

Let me know if you’d like me to elaborate on any specific changes mentioned in the commit messages!

📖 Chapters

Chapter 1: Introduction: This update addresses formatting inconsistencies by changing header styles and fixes a broken file path. It also incorporates feedback from Bravo to further refine the introduction chapter.
Chapter 2: ML Systems: Chapter 2 on ML Systems was significantly improved with updates to flow, content clarity, and accuracy. New sections were added on Mobile ML and Hybrid systems, including an example system for better understanding.
Chapter 3: DL Primer: Chapter 3’s “DL Primer” was reorganized with updated file structure and naming conventions for clarity. The chapter overview was also refined based on feedback and review.
Chapter 4: DNN Architectures: This update to Chapter 4 focuses on refining DNN architectures content. It includes additions like tables for other sections, system-level implications, and transformer architecture details, alongside extensive proofreading, formatting fixes, and reference corrections.
Chapter 5: AI Workflow: Chapter 5, “AI Workflow,” was significantly updated with a focus on clarifying the feedback loop process through a new figure and improved explanations. The chapter also underwent multiple revisions to define the problem stage and outline the ML lifecycle.
Chapter 6: Data Engineering: The purpose statement for Chapter 6: Data Engineering was updated to provide a clearer and more focused explanation of the chapter’s content.

Let me know if you need help summarizing any other Git commit messages! - Chapter 7: AI Frameworks: The purpose statement for Chapter 7: AI Frameworks was updated to provide a clearer and more accurate description of its content. This revision ensures readers understand the chapter’s focus on AI frameworks. - Chapter 8: AI Training: The purpose statement for Chapter 8: AI Training has been clarified and refined through multiple updates. This ensures the chapter’s objectives are clearly stated and understood by readers.

Let me know if you have any other Git commit messages you’d like me to summarize! - Chapter 9: Efficient AI: The Git commit messages indicate that the purpose statement for Chapter 9: Efficient AI was updated to improve clarity and focus. These revisions ensure the chapter’s goals are clearly defined for readers. - Chapter 10: Model Optimizations: Please provide the Git commit messages for Chapter 10: Model Optimizations (contents/core/optimizations/optimizations.qmd). I need the actual message text to generate a summary of the updates. - Chapter 11: AI Acceleration: Please provide me with the Git commit messages for Chapter 11: AI Acceleration (contents/core/hw_acceleration/hw_acceleration.qmd). I need the actual text of the commit messages to generate a summary of the updates.

Once you provide the commit messages, I can analyze them and give you a concise summary of the key changes and improvements. - Chapter 12: Benchmarking AI: Please provide the commit messages for Chapter 12: Benchmarking AI so I can generate a summary. - Chapter 13: ML Operations: This commit refines the purpose statement for Chapter 13: ML Operations, ensuring it clearly outlines the chapter’s goals and scope. The updated message also improves clarity and conciseness in the chapter description.

Let me know if you’d like a more detailed summary of specific changes! - Chapter 14: On-Device Learning: Please provide the Git commit messages for Chapter 14: On-Device Learning (contents/core/ondevice_learning/ondevice_learning.qmd). I need those messages to generate a summary of the updates. - Chapter 18: Robust AI: Chapter 18 was revised for clarity and accuracy, with improvements to figure placement, explanations of gradient norms and Bayesian Neural Networks (BNNs), and a refocusing on Machine Learning faults within the context of Robust AI. Additionally, redundant information was removed and transitions between concepts were smoothed. - Chapter 15: Security & Privacy: This update addresses redundancies in Chapter 15 by removing duplicate case studies and sections, ensuring clarity and focus. It also incorporates Bravo’s feedback to refine the chapter’s purpose. - Chapter 16: Responsible AI: The “Responsible AI” chapter’s purpose statement was refined to better reflect its focus on ethical considerations in AI development and deployment. This update clarifies the chapter’s scope and intended audience.

Let me know if you need help summarizing other Git commit messages! - Chapter 17: Sustainable AI: Chapter 17 on Sustainable AI was updated to clarify its purpose based on Bravo’s feedback. The changes refine the chapter’s focus and direction for greater clarity. - Chapter 19: AI for Good: This commit refines the chapter’s purpose to better reflect its focus on AI’s positive applications and impact on society. It also clarifies the intended audience and learning objectives for readers.

Let me know if you’d like me to elaborate on any specific changes within the commit messages! - Chapter 20: Conclusion: The conclusion for Chapter 20 was refined with some wording adjustments and an added reference to Chapter 4. These changes enhance clarity and provide better context within the book. - About: The “About” section was reorganized and updated to include Bloom’s Taxonomy. Content was also revised to reflect the addition of Chapter 4 and address various fixes.

Let me know if you need anything else! - Chapter: Dl Architectures: Chapter 3 on Deep Learning Architectures has been significantly revised to focus on machine learning systems, including reorganized content, updated learning objectives, and the addition of interactive Colab notebooks. The chapter also features a new cover image and refined references for improved clarity and accuracy. - Acknowledgements: The acknowledgements file was reorganized and updated to include logos and a list of contributors. Several commits also fixed filenames and ensured consistency in the README and acknowledgements file. - SocratiQ: This update incorporates bug fixes, such as resolving broken links and addressing an issue with Bravo, along with content improvements like adding an AI podcast and refining various text sections based on feedback.

Let me know if you’d like me to elaborate on any specific changes!

🧑‍💻 Labs

Hands-on Labs: Updated content with 0 changes
Raspberry Pi: Updated content with 0 changes

2024 Updates

📅 November 19 at 12:23 PM

📖 Chapters

Chapter 15: Security & Privacy: Chapter 15 on Security & Privacy has been updated with a new federated learning case study, clearer explanations of power consumption attacks and related figures, and improved organization of definitions and content. The chapter also benefits from less repetitive language and a more accessible writing style.
Chapter 16: Responsible AI: This update to Chapter 16 focuses on improving clarity and readability. Key changes include refining figure placements, correcting formatting inconsistencies, summarizing AI policies, and enhancing the explanation of a specific figure.
Chapter 17: Sustainable AI: This update to Chapter 17 refines the content on Sustainable AI with improved grammar, a new visual representation of the water footprint, and an updated figure illustrating the Life Cycle Assessment.
Chapter 19: AI for Good: This update to Chapter 19 focuses on improving the clarity and motivation for learning about TinyML within the “AI for Good” context. Minor grammatical errors were also corrected.
Acknowledgements: Several commits updated both the README and acknowledgements.qmd files to include contributions from various individuals. This reflects an ongoing effort to properly credit those who have helped develop the project.
SocratiQ: SocratiQ received several updates, including a new AI podcast feature, visual improvements like adding .png support for GIFs in PDFs and relocating button text, and updates to widget functionality. Additionally, text throughout the platform was refined for clarity.

📅 November 16 at 06:47 PM

📖 Chapters

Chapter 1: Introduction: Chapter 1’s introduction received several minor fixes. These include correcting a broken reference link, standardizing definition formatting, and resolving inconsistencies in styling.
Chapter 2: ML Systems: The introduction section in Chapter 2 on ML Systems has been renamed to “Overview” as it represents the primary introductory content for the chapter. This change clarifies the structure and purpose of the section.
Chapter 3: DL Primer: The introduction to Chapter 3 has been renamed to “Overview” to reflect the single introductory section present. This change streamlines the chapter’s structure for clarity.
Chapter 5: AI Workflow: This commit connected the various role sections within Chapter 5, focusing on AI workflow content.

Let me know if you’d like me to analyze more commit messages or provide a different kind of summary! - Chapter 6: Data Engineering: The introduction section in Chapter 6 has been renamed to “Overview” as it serves as the primary introductory content for the chapter. This change streamlines the organization and clarity of the chapter. - Chapter 7: AI Frameworks: The introduction in Chapter 7 was renamed to “Overview” as it served as the primary introductory section for AI frameworks.

This change simplifies the chapter’s structure and makes the content more clear. - Chapter 8: AI Training: The introduction section in Chapter 8 has been renamed to “Overview” as it serves as the primary introductory material for the chapter. This change aims to clarify the structure and content of the chapter. - Chapter 9: Efficient AI: The introduction section in Chapter 9 has been replaced with an overview, streamlining the chapter’s structure. This change focuses on providing a clearer and more concise starting point for readers. - Chapter 10: Model Optimizations: The introduction in Chapter 10 was replaced with an overview to streamline the content, as there was already a general introduction elsewhere.

This change focuses on clarity and avoiding redundancy. - Chapter 11: AI Acceleration: The introduction section in Chapter 11 has been replaced with an overview, streamlining the chapter’s content and focusing on the core aspects of AI acceleration. This change clarifies the chapter’s purpose and makes it easier for readers to understand its main points. - Chapter 12: Benchmarking AI: The introduction to Chapter 12 has been replaced with an “Overview” section, streamlining the chapter’s start. This change aims to provide a clearer and more focused introduction to the benchmarking process. - Chapter 13: ML Operations: Chapter 13 on ML Operations was reorganized and improved by grouping related topics, removing redundant information, and streamlining the data management section. The introduction was also revised from an abstract style to a more textbook-like approach. - Chapter 14: On-Device Learning: The introduction section in Chapter 14 has been replaced with an overview, streamlining the chapter’s structure.

This change focuses on clarity and conciseness by removing redundancy and providing a more direct introduction to the topic of on-device learning. - Chapter 18: Robust AI: The introduction in Chapter 18: Robust AI has been replaced with an overview, as it was determined that there was only one main introductory section. This change streamlines the chapter’s structure and focuses on providing a clear understanding of robust AI concepts. - Chapter 15: Security & Privacy: The introduction section in Chapter 15 was renamed to “Overview” as it now encompasses the initial explanation of the chapter’s content. This change aims for greater clarity and conciseness. - Chapter 16: Responsible AI: The Chapter 16 content on Responsible AI was updated with clearer explanations, improved definitions, and a restructured introduction now called “Overview” for better flow. These changes enhance the clarity and organization of this important topic. - Chapter 17: Sustainable AI: The introduction to Chapter 17: Sustainable AI was replaced with an overview due to its redundancy. This streamlining aims for a more focused and efficient presentation of the chapter’s content. - Chapter 19: AI for Good: The “Introduction” section in Chapter 19, AI for Good, has been renamed to “Overview” as it serves as the primary introduction to the chapter’s content. This change aims for clarity and conciseness. - Chapter 20: Conclusion: The introduction in Chapter 20 was renamed to “Overview” because it serves as the only introductory section for the chapter.

This change streamlines the chapter’s structure and clarifies its content. - Acknowledgements: The acknowledgments file was updated multiple times to include contributors and reorganize preface material. This work also involved fixing the way numbers were built within the file.

Let me know if you’d like me to elaborate on any specific aspect of the changes! - About: The “About” page’s file structure was reorganized for clarity and a relative path issue was fixed to ensure proper file loading.

Let me know if you have any other text snippets you’d like summarized!

🧑‍💻 Labs

Arduino: Updated content with 0 changes
Seeed XIAO ESP32S3: Updated content with 0 changes
Raspberry Pi: Updated content with 0 changes

📅 November 15 at 09:29 PM

📖 Chapters

Chapter 1: Introduction: The Introduction chapter was significantly revised, including updated definitions, improved text flow and clarity, the addition of case studies with multimedia links, and integration of feedback from reviewers.

Formatting inconsistencies were also addressed for a polished final product. - Chapter 2: ML Systems: Chapter 2’s content was reorganized, changing the “Introduction” to an “Overview” and removing the previous labs section. A new “labs” folder has been created alongside the existing “core” folder for better organization.

Let me know if you have any other text snippets you’d like summarized! - Chapter 3: DL Primer: The Chapter 3 Git commit messages indicate structural changes to the DL Primer. The “Introduction” section was renamed to “Overview,” and lab exercises were moved to a dedicated “labs” folder within a newly created “core” folder. - Chapter 5: AI Workflow: The Chapter 5 content was reorganized, separating the “labs” into a dedicated folder while integrating role descriptions within their respective sections. This clarifies the structure and improves navigation for users. - Chapter 6: Data Engineering: The Chapter 6 content was restructured, moving the “Introduction” to an “Overview” and separating lab exercises into their own “labs” folder. This change aims to improve organization and clarity within the chapter. - Chapter 7: AI Frameworks: The Chapter 7 content was restructured by replacing the introduction with an overview and removing lab sections. A new “labs” folder was created to house related materials, improving organization within the chapter. - Chapter 8: AI Training: The Chapter 8 content was reorganized to improve clarity, replacing the “Introduction” with an “Overview” and removing the lab sections. Dedicated folders for “labs” and “core” were created to better structure the material. - Chapter 9: Efficient AI: The Chapter 9 content was restructured, replacing the introduction with an overview and removing the lab sections. Labs were moved to a new “labs” folder within the “core” directory. - Chapter 10: Model Optimizations: The Chapter 10 content was reorganized, replacing the introduction with an overview and removing lab sections. Labs have been moved into their own dedicated “labs” folder within the “core” directory structure. - Chapter 11: AI Acceleration: The “Chapter 11: AI Acceleration” content was restructured, renaming the introduction to “Overview” and removing lab sections. A new directory structure was implemented with dedicated folders for “labs” and “core” content. - Chapter 12: Benchmarking AI: Chapter 12, Benchmarking AI, now features an improved overview and streamlined content with removed repetitive sections and descriptions. Key updates include a reworked trifecta diagram, revised examples, and a new section on energy benchmarking in historical context. - Chapter 13: ML Operations: Chapter 13 has been reorganized and streamlined, with fragmented topics grouped, redundant information removed, and the data management section clarified. The chapter also adopts a more consistent textbook style and lab exercises have been moved to separate folders. - Chapter 14: On-Device Learning: Chapter 14 was reorganized with a clearer overview, improved explanations of concepts like IID and pruning, and distinctions made between on-device learning and federated learning. Outdated lab sections were removed to focus on core content. - Chapter 18: Robust AI: The Chapter 18 content was reorganized, replacing the original introduction with an overview and moving the lab exercises to a separate “labs” folder within “core”. This restructuring aims for clearer content organization and separation of theoretical material from practical exercises. - Chapter 15: Security & Privacy: Chapter 15 on Security & Privacy has been reorganized with an updated “Overview” replacing the original Introduction. The lab exercises have been removed from the chapter content and placed in a dedicated “labs” folder. - Chapter 16: Responsible AI: Chapter 16 on Responsible AI was restructured to improve clarity and organization. The introduction was renamed “Overview,” the lab section was removed, and dedicated folders were created for labs and core content. - Chapter 17: Sustainable AI: The Chapter 17 content was reorganized, renaming the introduction to an “Overview” and removing the labs section. A new “labs” folder was created within the “core” directory to house lab materials separately. - Chapter 19: AI for Good: The “AI for Good” chapter was restructured to replace the introductory section with an overview and remove lab exercises. A new directory structure was also implemented, separating labs into their own folder. - Chapter 20: Conclusion: The commit messages indicate that Chapter 20’s “Introduction” section was renamed to “Overview” as it serves as the sole introduction. Additionally, new folders named “labs” and “core” were created within the chapter’s directory structure. - Acknowledgements: The commit reorganized the project’s structure by creating dedicated “labs” and “core” folders. This change aims to better categorize and manage different aspects of the project. - SocratiQ: The initial draft of the SocratiQ bot was created, laying the foundation for its future development. This commit establishes the basic structure and functionality of the bot within the contents/ai/socratiq.qmd file.

Let me know if you’d like a more detailed summary or analysis of specific changes! - SocratiQ: The initial draft of the SocratiQ bot was created, establishing its foundation within the contents/llm/socratiq.qmd file format. This setup paves the way for further development and integration of the bot’s functionality. - Chapter 19: AI for Good: This update refactors the “AI for Good” chapter by creating dedicated “labs” and “core” folders to better organize content. The main AI4Good section itself was also updated with unspecified improvements. - Chapter 18: Robust AI: This update focuses on establishing a foundational structure for Chapter 18 on Robust AI by creating dedicated “labs” and “core” folders. The content itself has also been updated with improvements to the “robustAI” section. - Chapter 17: Sustainable AI: The “Sustainable AI” chapter content was updated by creating new “labs” and “core” folders for better organization, and making relevant changes to the text. - Chapter 16: Responsible AI: This update establishes a new “labs” and “core” folder structure within the “responsible_ai” directory. The content of the responsibleAI.qmd file was also updated to reflect changes.

Let me know if you’d like more detail on any specific commit message! - Chapter 15: Security & Privacy: This update focused on enhancing the privacy and security chapter by addressing suggested fixes, renaming images for better privacy, and adding details to the TEE section. Minor mistakes were also removed for improved clarity. - Chapter 13: ML Operations: This update establishes the foundational structure for Chapter 13 by creating dedicated “labs” and “core” folders. It also incorporates significant improvements to the content on Machine Learning Operations (MLOps).

Let me know if you’d like me to elaborate on any specific aspect of these changes! - Chapter 14: On-Device Learning: This update adds dedicated “labs” and “core” folders for Chapter 14 on On-Device Learning. It also includes improvements to the on-device learning content and the BibTeX bibliography formatting. - Chapter 12: Benchmarking AI: This update established new “labs” and “core” folders for organization, then focused on improving the content related to AI benchmarking within the “benchmarking.qmd” file.

Let me know if you’d like me to elaborate on any specific aspect of these changes! - Chapter 11: AI Acceleration: This update establishes a framework for Chapter 11 by creating dedicated “labs” and “core” folders within the “hw_acceleration” directory. The AI hardware acceleration section was also updated with new content. - Chapter 10: Model Optimizations: Chapter 10 on model optimizations was updated with new content, including lab exercises and core functionality improvements. Various fixes were also implemented based on feedback and to ensure consistency in formatting throughout the chapter. - Chapter 9: Efficient AI: The Chapter 9 “Efficient AI” content was updated to include new lab exercises and improved information about AI efficiency. These changes will help readers understand and implement practical techniques for making AI models more efficient. - Chapter 8: AI Training: This update establishes foundational structure for Chapter 8 by creating dedicated “labs” and “core” folders within the “training” section. The chapter content itself was also updated to reflect these changes and provide relevant training material. - Chapter 7: AI Frameworks: This update restructured the Chapter 7 content by creating dedicated “labs” and “core” folders. It also included updates to the information about various AI frameworks covered in the chapter. - Chapter 6: Data Engineering: Chapter 6 on Data Engineering was updated with new content, including the creation of dedicated “labs” and “core” folders for organization. The chapter itself also received revisions for improved clarity and accuracy. - Chapter 5: AI Workflow: This update organizes Chapter 5 content by creating dedicated “labs” and “core” folders within the “workflow” directory. The AI workflow itself has also been updated with unspecified improvements.

Let me know if you need any further elaboration on specific commits! - Chapter 3: DL Primer: The Chapter 3: DL Primer was updated with new content, including the creation of dedicated “labs” and “core” folders for organization. The main focus of the update was improving the depth and clarity of the deep learning primer itself. - Chapter 2: ML Systems: Chapter 2 on ML Systems was updated with new content, including labs and core folders, as well as revised learning objectives and an introduction broadened beyond embedded systems.

This summary captures the most important changes: new structural elements (labs/core folders), content revisions (“updated ML systems”), learning objective updates, and a shift in focus for the introduction. - Chapter 1: Introduction: The introduction chapter was updated with revised content and writing improvements. Additionally, new “labs” and “core” folders were created to better organize the project’s structure.

🧑‍💻 Labs

Hands-on Labs: Updated content with 0 changes
Arduino: Updated content with 0 changes
Seeed XIAO ESP32S3: Updated content with 0 changes
Raspberry Pi: Updated content with 0 changes

📅 September 20 at 07:26 AM

📖 Chapters

Chapter 3: DL Primer: Chapter 3, “DL Primer”, has been updated with several crucial revisions including fixing broken links and references throughout the chapter, resolving formatting issues, and completing all chapters. These changes ensure accuracy and clarity for readers learning about deep learning fundamentals.
Chapter 19: AI for Good: This update fixes broken references and figures in Chapter 19: AI for Good, ensuring all content is accurate and visually consistent. The chapter is now finalized and merged into the main branch.
Chapter 6: Data Engineering: The main updates for Chapter 6: Data Engineering include formatting corrections, a figure reference adjustment, and final revisions to ensure all chapters are complete.
Chapter 11: AI Acceleration: This update focuses on finalizing Chapter 11: AI Acceleration by correcting character formatting, fixing figure references, and ensuring all content is complete.
Chapter 10: Model Optimizations: This update addresses character formatting within Chapter 10’s Model Optimizations by correcting instances of ’ with the standard single quotation mark ’.

Let me know if you need further assistance summarizing these changes or have any other questions! - Chapter 8: AI Training: The Chapter 8 commit addressed a formatting issue by replacing single apostrophes with standard double quotes. This ensures consistent character usage throughout the chapter on AI training. - Chapter 1: Introduction: This update focuses on finalizing Chapter 1, addressing figure reference issues, and incorporating revisions from other chapters. The chapter now includes all necessary content and is ready for integration into the larger project. - Chapter 9: Efficient AI: Chapter 9, “Efficient AI”, has been finalized with all figures properly referenced and the chapter now complete. This update signifies the completion of all chapters in the project. - Chapter 14: On-Device Learning: Chapter 14 on On-Device Learning has been finalized with fixes to references and paths throughout the content.

This ensures all links and navigation within the chapter are accurate and functional for readers. - Chapter 5: AI Workflow: Chapter 5, “AI Workflow,” has been updated to fix broken figure references and ensure all content is finalized. The chapter is now complete. - Chapter 7: AI Frameworks: The “Chapter 7: AI Frameworks” section was updated to fix figure references and ensure all chapters are now complete. This revision completes the content for all chapters. - Chapter 13: ML Operations: Chapter 13 was updated to fix figure references and include all completed chapters. The chapter content is now finalized with the integration of revised figures from the ‘dev’ branch. - Chapter 15: Security & Privacy: The “Security & Privacy” chapter was updated with revised content to reflect the completion of all chapters.

This update also included resolving merge conflicts from other chapters, ensuring consistency across the entire document. - Chapter 17: Sustainable AI: Chapter 17 on Sustainable AI was updated with revisions for all chapters, including proofreading and corrections to figures and references. This ensures accuracy and clarity in this important section. - Chapter 12: Benchmarking AI: Chapter 12 “Benchmarking AI” has been updated with formatting fixes, removal of unnecessary figures, and resolution of merge conflicts from other chapters to ensure all content is consistent and up-to-date. The chapter is now complete. - Chapter 2: ML Systems: The “Chapter 2: ML Systems” content was revised and updated, including fixes to figure references. All chapters are now complete.

Let me know if you’d like me to elaborate on any specific commit message!

🧑‍💻 Labs

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📅 September 12 at 10:16 AM

📖 Chapters

Chapter 20: Conclusion: Based on the commit messages provided, the main update for Chapter 20 is the incorporation of feedback from Baldo to improve the conclusion section.

Let me know if you’d like me to elaborate on any specific aspect of the changes! - Chapter 13: ML Operations: The commits for Chapter 13: ML Operations incorporated feedback from Baldo to refine the content and improve clarity.

Let me know if you’d like a more detailed summary or want to focus on specific aspects of the changes! - Chapter 19: AI for Good: This commit fixes various issues in Chapter 19: AI for Good, primarily addressing contributions from Baldo. The chapter now benefits from improved accuracy and clarity.

Let me know if you’d like a more detailed breakdown of the specific changes! - Chapter 18: Robust AI: Chapter 18, “Robust AI”, has been updated with fixes identified and implemented by (BravoBaldo?). These changes improve the accuracy and clarity of the content within the chapter. - Chapter 17: Sustainable AI: Chapter 17 on Sustainable AI was updated with formatting fixes and improvements to indentation, thanks to feedback from (BravoBaldo?).

These changes ensure clear presentation and readability of the content.

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📅 September 06 at 07:18 AM

📖 Chapters

Chapter 16: Responsible AI: This commit makes several corrections to the bibliography and text within Chapter 16 on Responsible AI. The primary focus was ensuring accuracy and clarity in both factual information and wording.

📅 September 04 at 08:30 PM

📖 Chapters

Chapter 1: Introduction: The introduction chapter now has correctly formatted captions for all images, ensuring visual consistency across even-numbered pages.
Chapter 15: Security & Privacy: Chapter 15 on Security & Privacy was updated with several grammar corrections and refinements to ensure clarity and accuracy.
Chapter 19: AI for Good: This update to Chapter 19 on AI for Good focuses primarily on grammatical improvements throughout the content. These revisions enhance the clarity and readability of the chapter.
Chapter 12: Benchmarking AI: This commit primarily focuses on grammar corrections within Chapter 12: Benchmarking AI, ensuring clarity and accuracy in the content.
Chapter 20: Conclusion: The conclusion chapter in “Chapter 20” was updated to include grammar fixes for improved clarity and readability.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 6: Data Engineering: This update addresses grammar issues within Chapter 6’s content on Data Engineering to ensure clarity and accuracy. - Chapter 3: DL Primer: This commit focuses on improving the clarity and grammatical correctness of Chapter 3: DL Primer. Minor grammar fixes were implemented to enhance readability and accuracy. - Chapter 7: AI Frameworks: Minor grammar corrections were made to the Chapter 7 content on AI frameworks in the contents/frameworks/frameworks.qmd file.

Let me know if you’d like me to elaborate on any specific changes! - Chapter 11: AI Acceleration: The Chapter 11 content on AI acceleration has been improved with grammar fixes and more detailed explanations for better understanding. These changes enhance the clarity and accuracy of the information presented. - Chapter 2: ML Systems: This update focuses on improving the grammar and clarity of Chapter 2: ML Systems. The content has been refined to ensure accuracy and readability.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 14: On-Device Learning: The Chapter 14 content on On-Device Learning was updated with grammatical fixes to improve clarity and readability.

Let me know if you’d like me to elaborate on any specific commit or aspect of the changes! - Chapter 13: ML Operations: Minor grammatical errors were corrected in Chapter 13: ML Operations to improve readability and clarity. - Chapter 10: Model Optimizations: This update focuses on grammatical improvements within Chapter 10: Model Optimizations.

Let me know if you’d like a more detailed summary or have other Git commit messages to analyze! - Chapter 16: Responsible AI: The “Responsible AI” chapter in the book received grammatical fixes to improve clarity and readability. - Chapter 18: Robust AI: This update to Chapter 18: Robust AI focuses on improving the text quality through grammar fixes, ensuring clarity and accuracy in the content. - Chapter 17: Sustainable AI: This commit focuses solely on grammar and phrasing improvements within Chapter 17, “Sustainable AI,” ensuring clarity and accuracy in the text. There are no substantive changes to content. - Chapter 8: AI Training: This update to Chapter 8 focuses on grammar corrections within the “training” section of the document, ensuring clarity and accuracy in the content. - Chapter 9: Efficient AI: The Chapter 9 commit messages indicate that the “Efficient AI” chapter has received improved explanations for better understanding of the content.

Let me know if you’d like me to elaborate on any specific commit message!

🧑‍💻 Labs

Arduino: Updated content with 0 changes

📅 September 02 at 08:19 PM

📖 Chapters

Chapter 11: AI Acceleration: The Chapter 11 commit for AI Acceleration focused on enhancing clarity and accessibility for students. This includes fixing table formatting issues and providing more student-focused explanations of hardware design principles within the introduction.
Chapter 2: ML Systems: This update addresses a grammatical error in Chapter 2’s content about ML systems by fixing a dangling sentence. Special thanks to (shreyasgrampurohit?) for identifying and resolving this issue.

Let me know if you have any other Git commit messages you’d like summarized! - Chapter 13: ML Operations: This update to Chapter 13 on ML Operations introduces a new section on model serving, addresses feedback from reviewers, and includes various refinements such as content improvements, typo fixes, and figure additions.

🧑‍💻 Labs

Raspberry Pi: Updated content with 0 changes

📅 August 29 at 11:14 PM

📖 Chapters

Chapter 13: ML Operations: Updates to Chapter 13: ML Operations were made to address feedback from BravoBaldo, improving the clarity and accuracy of the content. These fixes enhance the chapter’s educational value for readers learning about ML Operations.
Chapter 14: On-Device Learning: Updates to Chapter 14: On-Device Learning were made based on feedback from (BravoBaldo?), ensuring improved clarity and accuracy of the content. These revisions refine the chapter’s explanation of on-device learning concepts.

Let me know if you’d like me to elaborate on any specific changes mentioned in the commit messages!

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📅 August 27 at 12:28 PM

📖 Chapters

Chapter 12: Benchmarking AI: This update fixes issues in Chapter 12: Benchmarking AI, specifically addressing feedback from (BravoBaldo?) to improve the content’s accuracy and clarity.

Let me know if you would like me to elaborate on any specific commit message! - Chapter 10: Model Optimizations: Chapter 10 on Model Optimizations was refined by removing redundant information, clarifying knowledge distillation techniques, and improving challenge descriptions for better learning. The historical background and formatting were also adjusted for conciseness and clarity. - Chapter 9: Efficient AI: Chapter 9, “Efficient AI,” was updated with clearer explanations of floating point representation and structure importance methods, along with corrections to formatting errors and image references. Student feedback from Chapter 8 was also incorporated into the revision. - Chapter 7: AI Frameworks: This update fixes formatting issues in a table and resolves broken links within the Chapter 7 content on AI Frameworks. These changes ensure improved readability and accuracy of the information presented. - Chapter 15: Security & Privacy: The Chapter 15 on Security & Privacy was updated to include revisions to the Power Attack and Side-Channel Attack sections, along with the fixing of broken links within the chapter. - Chapter 13: ML Operations: This update includes minor wording changes to improve clarity and readability in Chapter 13: ML Operations. The focus was on refining the text for better understanding of the ML Ops concepts presented. - Chapter 11: AI Acceleration: Chapter 11 on AI Acceleration was updated to fix broken links, correct inaccuracies in the text like hyphens and a duplicate title, and ensure clarity by completing an incomplete sentence. This update improves the accuracy and readability of the content. - Chapter 17: Sustainable AI: The Chapter 17: Sustainable AI content has been updated to fix any broken links within the document. This ensures smooth navigation and access to all relevant information for readers.

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📅 August 22 at 11:13 AM

📖 Chapters

Chapter 19: AI for Good: The commit messages describe formatting changes for subscripts within Chapter 19’s content. This update ensures proper visual representation of mathematical notations and potentially other technical terms.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 11: AI Acceleration: Please provide the Git commit messages so I can generate a summary for you. - Chapter 17: Sustainable AI: The commit updates Chapter 17 on Sustainable AI by adding subscripts to various terms for improved clarity and readability. This enhances the overall presentation and understanding of the content related to sustainable AI practices.

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📅 August 21 at 09:47 PM

📖 Chapters

Dsp Spectral Features Block: This commit removes unnecessary code that was no longer in use within the Dsp Spectral Features Block. This cleanup improves the efficiency and maintainability of the code.
Lab: Arduino Image Classification: This commit cleans up the “Lab: Arduino Image Classification” project by removing unused code and making enhancements for improved functionality.
Chapter 10: Model Optimizations: Chapter 10: Model Optimizations received several crucial bug fixes and enhancements, addressing typos and implementing pivotal improvements for better accuracy and performance. These changes solidify the chapter’s content, ensuring clarity and effectiveness for readers.
Chapter 6: Data Engineering: Several typographical errors were corrected, and improvements were made to enhance clarity and accuracy within Chapter 6 on Data Engineering. These revisions ensure a more polished and informative learning experience for readers.
Chapter 7: AI Frameworks: This update to Chapter 7: AI Frameworks includes several refinements, such as fixing typos and improving the wording for clarity and accuracy. Additionally, some content related to “delve” was revised and incorporated.

Let me know if you’d like a more detailed breakdown of any specific commit message! - Chapter 11: AI Acceleration: The “Chapter 11: AI Acceleration” section was updated with several improvements, including fixing typos and references, enhancing content, and converting tables to a more user-friendly grid format. These changes enhance clarity and readability for readers exploring hardware acceleration in AI. - Chapter 14: On-Device Learning: The Chapter 14 content on On-Device Learning was updated to include several minor fixes, such as correcting typos and improving wording. Additionally, a grid table was added for better organization and presentation of information.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 13: ML Operations: Chapter 13 on ML Operations was updated with several visual improvements. This includes fixing typographical errors, updating table references and styling, and refining the grid table for better readability. - Chapter 15: Security & Privacy: Several improvements were made to Chapter 15 on Security & Privacy, including fixing typos and table references, enhancing the visual presentation with striped and hovered tables, and incorporating bug fixes. The chapter was also updated to match the latest version of the dev branch for consistency. - Chapter 8: AI Training: This update to Chapter 8: AI Training focuses on improving readability and accuracy. It addresses several minor issues, including inconsistent formatting, broken links, and inaccurate references, while also enhancing the presentation with a grid table for improved clarity. - Chapter 2: ML Systems: This update to Chapter 2 on ML Systems includes several key fixes, including addressing typos, enhancing certain elements, and implementing pivotal changes for improved accuracy and clarity. The chapter now provides a more robust and informative overview of ML systems. - Chapter 18: Robust AI: This update to Chapter 18, “Robust AI”, primarily focused on improving visual presentation and accuracy. It fixed a citation reference issue and enhanced the appearance of tables by adding styling for better readability. - Chapter 19: AI for Good: The commit message “fix enhance” doesn’t provide specific details about the changes made to Chapter 19: AI for Good. It’s too general to summarize the content updates effectively.

To get a useful summary, you’d need more descriptive commit messages that explain what was fixed and how it was enhanced. - Chapter 12: Benchmarking AI: Several enhancements were made to Chapter 12 on Benchmarking AI, including bug fixes and improvements to the utilization of certain functionalities within the chapter.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 3: DL Primer: Several enhancements and bug fixes were implemented in Chapter 3’s “DL Primer” section. These changes primarily focus on improving accuracy and clarity within the content. - Chapter 9: Efficient AI: Fixes were made to “Enhance” content within Chapter 9: Efficient AI, including addressing issues found in the delve section. - Chapter 1: Introduction: The Introduction chapter received several bug fixes and enhancements to improve clarity and accuracy.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 16: Responsible AI: The Chapter 16 content on Responsible AI has been enhanced by switching from a basic list format to a clearer and more organized grid table. This improves readability and makes it easier for users to understand the information presented. - Chapter 17: Sustainable AI: The Sustainable AI chapter received several enhancements, including bug fixes, improved utilization of resources, and deeper exploration of the topic.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 5: AI Workflow: This commit batch addresses several issues and enhancements within Chapter 5’s AI Workflow content. Key fixes were implemented alongside refinements to improve clarity and accuracy.

Let me know if you need more details on specific commits! 😊

🧑‍💻 Labs

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📅 August 15 at 03:57 PM

📖 Chapters

Chapter 11: AI Acceleration: This update focuses on improving the presentation of information in Chapter 11 by replacing tables with more interactive and user-friendly grid tables. Several fixes were also made to ensure accuracy and functionality.
Chapter 13: ML Operations: The Chapter 13 Git commits focused primarily on improving the visual presentation of tables. Styling changes were made to include striping, hovering effects, and grid structures for enhanced readability and aesthetics.
Chapter 15: Security & Privacy: The primary focus of these updates for Chapter 15 was improving the visual presentation and structure of tables. This includes using grid tables, adding styling classes for cleaner appearance, and fixing references within the table content.
Chapter 18: Robust AI: This update to Chapter 18 addresses several minor issues, including fixing a citation reference problem and enhancing the appearance of tables with striped rows and hover effects.

It also includes some general improvements for clarity and consistency. - Chapter 8: AI Training: Chapter 8 on AI Training was updated with improvements to content clarity, formatting, and technical accuracy. Key changes include addressing broken links, refining regularization and hyperparameter search explanations, and updating NN notation for better comprehension. - Chapter 19: AI for Good: The commit messages “fix” and “enhance” suggest minor bug fixes and improvements were made to Chapter 19: AI for Good. These updates likely focused on enhancing clarity, accuracy, or functionality within the content.

Let me know if you have any other Git commit messages you’d like summarized! - Chapter 12: Benchmarking AI: Several enhancements and bug fixes were made to Chapter 12, focusing on improving the accuracy and clarity of benchmarking AI concepts within the “benchmarking.qmd” file.

This summary captures the essence of the commit messages without going into unnecessary detail. - Chapter 6: Data Engineering: This update to Chapter 6 focuses on significant bug fixes and enhancements related to data engineering concepts. The revisions ensure accuracy, clarity, and overall improvement in the chapter’s content.

Let me know if you need help summarizing other sets of commit messages! - Chapter 3: DL Primer: This update focuses on fixing issues and enhancing content within the “DL Primer” chapter, specifically addressing several errors and improving clarity. - Chapter 9: Efficient AI: This update for Chapter 9, “Efficient AI,” focuses on refining and improving content. Specific changes include fixing errors, making thoughtful deletions, and incorporating revisions from the “dev” branch to enhance the overall quality of the chapter. - Chapter 7: AI Frameworks: This update to Chapter 7 on AI Frameworks focused on addressing typos and improving clarity within the “frameworks.qmd” file.

Let me know if you’d like me to elaborate on any specific commit message! - Lab: Arduino Image Classification: This commit enhances the Lab: Arduino Image Classification workflow with bug fixes and performance improvements.

Let me know if you have any other Git commit messages you’d like summarized! - Chapter 1: Introduction: Several enhancements were made to Chapter 1’s introduction, including addressing some “delve fixes” for improved clarity and accuracy.

Let me know if you’d like me to elaborate on any specific changes mentioned in the commit messages! 😊 - Chapter 2: ML Systems: This update to Chapter 2: ML Systems focuses on crucial fixes and enhancements for improved clarity and functionality within the content. Key improvements include addressing pivotal issues and leveraging best practices for optimal user experience.

Let me know if you have more Git commit messages and need a summary! 😊 - Chapter 14: On-Device Learning: The Chapter 14 content on On-Device Learning was enhanced with several improvements, including fixing issues, utilizing grid tables for better organization, and enhancing clarity.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 10: Model Optimizations: Chapter 10 “Model Optimizations” received several crucial updates. These included pivotal bug fixes, enhancements to existing code for improved utilization, and further refinement of delve functionalities. - Chapter 16: Responsible AI: The content for Chapter 16 on Responsible AI has been improved by switching from a basic list format to a more organized and visually appealing grid table. This enhances readability and comprehension of the information presented.

Let me know if you’d like me to elaborate on any specific aspect of the changes! - Chapter 17: Sustainable AI: Several enhancements were made to Chapter 17, focusing on improving clarity and accuracy regarding sustainable AI practices. These updates include fixing issues, utilizing better language, and delving deeper into relevant concepts.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 5: AI Workflow: Fixes and enhancements were made to the AI Workflow chapter in Chapter 5. The changes focused on improving the clarity and accuracy of the workflow descriptions.

Let me know if you’d like me to elaborate on any specific commit message!

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📅 August 06 at 09:39 PM

📖 Chapters

Dsp Spectral Features Block: This update fixes issues with image width display in PDF renditions generated from the Dsp Spectral Features Block QMD file.

Let me know if you’d like a more detailed summary! - Lab: Arduino Image Classification: This update addresses several issues related to PDF rendering and video links. It fixes image width problems in PDFs, resolves broken video links, and removes unnecessary formatting. - Chapter 7: AI Frameworks: Chapter 7 on AI Frameworks was updated with improved content, including a more comprehensive conclusion and explanations on advanced features. Various formatting and style improvements were also made to enhance readability and consistency across the chapter. - Chapter 13: ML Operations: This update focuses on improving the visual presentation and accuracy of Chapter 13. It fixes broken URL links, standardizes table formatting with a grid layout and left alignment, and ensures consistent credit attribution. - Chapter 18: Robust AI: This update focuses on improving the visual presentation of Chapter 18: Robust AI. It includes changes to table formatting, alignment, and source attribution, as well as implementing HTML and PDF builds for improved readability. - Chapter 5: AI Workflow: Chapter 5 content was updated to incorporate grid formatting for tables, improving their visual presentation and consistency. Student feedback was also integrated into the workflow section. - Chapter 3: DL Primer: Chapter 3 received significant updates, including fixing broken URL links, implementing grid tables for improved presentation, and refining text wording for clarity and consistency.

Additionally, formatting styles were standardized, and credit sections were revised. - Chapter 6: Data Engineering: Chapter 6 on Data Engineering was updated with improved formatting, including grid tables, left alignment for tables, and consistent styling for citations. New content includes an exercise using Wake Vision Colab. - Chapter 15: Security & Privacy: The privacy and security section was revised for accuracy and clarity, and all broken links were repaired due to previous formatting issues. - Chapter 19: AI for Good: This update for Chapter 19 focuses on fixing broken URL links and improving consistency. It also includes HTML and PDF builds, specifically tailored for Edward Tufte’s style guide.

Let me know if you need further assistance with summarizing Git commits! - Chapter 11: AI Acceleration: Chapter 11’s content has been improved by fixing all broken URL links and standardizing credit and source citations for a cleaner, more professional presentation. - Chapter 14: On-Device Learning: Chapter 14, “On-Device Learning”, has been updated with several improvements. This includes fixing all broken URL links, implementing grid tables for better visual organization, aligning table content left for consistency, and standardizing the formatting of credits/sources. - Chapter 16: Responsible AI: This update fixes all broken URL links in Chapter 16 on Responsible AI, standardizes source citations, and adds HTML and PDF build options for Edward Tufte’s style. - Chapter 8: AI Training: This update primarily fixes broken links in the Chapter 8 content, ensures consistent formatting for “Credit” sections, and introduces grid tables with left alignment for improved readability. - Chapter 9: Efficient AI: This update focuses on visual improvements within Chapter 9, Efficient AI. It includes left-aligned grid tables with consistent markdown formatting, updated source citations, and corrections to image paths and figure IDs. - Chapter 2: ML Systems: This update focuses on improving the visual presentation of Chapter 2. It includes left alignment for tables, updated credit formatting for consistency, and added HTML and PDF build capabilities for Edward Tufte’s style.

Let me know if you’d like me to elaborate on any specific change! - Chapter 10: Model Optimizations: This update focuses on visual improvements for Chapter 10, including aligning tables left, shortening table widths, and standardizing formatting styles. Additional changes include adding in-text citations and generating HTML and PDF versions for better readability. - Chapter 12: Benchmarking AI: The commit message indicates that credit attribution in Chapter 12 (“Benchmarking AI”) was updated to “Source:” for consistency, and the formatting style throughout the chapter was improved. - Chapter 17: Sustainable AI: This update focuses on improving consistency and presentation within Chapter 17, “Sustainable AI.” It standardizes credit formatting and adds HTML and PDF build options for better accessibility. - Chapter 1: Introduction: This commit adds HTML and PDF build functionality to Chapter 1’s introduction content, allowing for easy sharing and distribution in various formats. The implementation was specifically tailored for Edward Tufte’s style guide.

🧑‍💻 Labs

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📅 June 25 at 07:01 AM

📖 Chapters

Chapter 3: DL Primer: The main update to Chapter 3: DL Primer is the correction of a broken video link in section 3.1.

📅 June 20 at 09:33 PM

📖 Chapters

Chapter 2: ML Systems: The Chapter 2: ML Systems content was updated to address feedback from students, specifically resolving a broken reference and incorporating changes from the ‘dev’ branch. These improvements enhance the accuracy and user experience of the chapter.

🧑‍💻 Labs

Shared: Updated content with 0 changes

📅 June 19 at 05:05 PM

📖 Chapters

Chapter 12: Benchmarking AI: The Chapter 12 content on Benchmarking AI was updated with improved formatting, including citation style changes and line spacing fixes. Additional figures were added to illustrate training progress in MLPerf benchmarks.
Chapter 6: Data Engineering: This update to Chapter 6: Data Engineering focuses on improving the presentation and consistency of the content. It includes fixes for citation formatting and addresses issues identified by Markdown linters.

Let me know if you’d like a more detailed breakdown of any specific changes! - Chapter 11: AI Acceleration: This update to Chapter 11 focuses on improving readability and accuracy. It includes fixing citation formatting, addressing Markdown linting issues, and adding a link to Google’s Edge TPU website for further information. - Chapter 10: Model Optimizations: Chapter 10’s content on model optimizations received minor updates for improved readability. These changes included fixing citation formatting and addressing several typos and formatting inconsistencies. - Chapter 18: Robust AI: The Chapter 18 Qmd file has been updated with corrected citation formatting, switching from parentheses to square brackets, and minor style improvements were made using MD lint. - Acknowledgements: This update focuses on improving code quality and readability within the acknowledgements file. It includes applying MD lint fixes and disabling comments on specific pages for cleaner presentation. - Chapter 19: AI for Good: This commit made minor style and formatting improvements to Chapter 19: AI for Good using Markdown linting tools.

Let me know if you’d like me to elaborate on any specific changes within the commit! - Chapter 20: Conclusion: This commit includes minor text fixes using MD lint to ensure consistency and readability in Chapter 20’s conclusion.

Let me know if you need me to analyze more Git commits! - Chapter 3: DL Primer: This update to Chapter 3: DL Primer focuses on refining the text for clarity and consistency. Several typos, formatting issues, and redundancies have been addressed through a series of revisions. - Chapter 9: Efficient AI: This update includes minor fixes for Markdown formatting (lint) and ensures all video references in Chapter 9 are correctly linked. - Chapter 7: AI Frameworks: This update to Chapter 7: AI Frameworks focuses on improving readability and accuracy. It includes various typo and formatting corrections identified by MD lint. - Lab: Arduino Image Classification: This commit includes minor code style improvements identified by Markdown linting tools. - Chapter 1: Introduction: The Introduction chapter was updated with revisions based on feedback from the Data Review team, including improvements to the text and removal of the foreword. Minor fixes for Markdown linting and an error in a file reference were also addressed. - Chapter 2: ML Systems: Chapter 2: ML Systems was updated with several improvements based on feedback from both reviewers and data reviews. These changes include content refinements and fixes to ensure clarity and accuracy. - Chapter 14: On-Device Learning: This update includes minor code style improvements identified by the MD lint tool to enhance readability and consistency within the Chapter 14 content on On-Device Learning. - Chapter 13: ML Operations: This update includes MD lint fixes for Chapter 13: ML Operations, ensuring consistency and readability in the content. - Chapter 15: Security & Privacy: This update addresses minor formatting issues in Chapter 15 by fixing case study headers and applying MD lint fixes for improved readability and consistency. - Chapter 16: Responsible AI: Minor text formatting issues were addressed in Chapter 16: Responsible AI using MD lint fixes to ensure consistency and clarity. - Chapter 17: Sustainable AI: This update includes minor text formatting fixes for Chapter 17: Sustainable AI to ensure consistency and readability.

Let me know if you’d like a more detailed breakdown of the specific changes! 😊 - Chapter 8: AI Training: This update addresses several typos and formatting issues within Chapter 8’s content on AI Training, enhancing the clarity and readability of the material.

The primary focus was ensuring grammatical accuracy and consistent formatting throughout the chapter. - Chapter 5: AI Workflow: Minor code style improvements were made to the Chapter 5: AI Workflow content using Markdown linting tools. - Dsp Spectral Features Block: The DSP Spectral Features Block documentation received minor updates including fixes to resource references and a slight adjustment to the title for clarity. - Object Detection Fomo: The Object Detection FOMO code has been integrated into the “labs” environment, likely for testing or further development. This integration allows for more extensive experimentation and refinement of the object detection capabilities within this framework. - Generative Ai: The provided commit messages only contain minor wording adjustments (“Wording tweak” and “wording tewak”).

There’s no information about significant changes or improvements to Generative AI functionality in these commits.

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📅 June 11 at 04:08 PM

📖 Chapters

Chapter 11: AI Acceleration: This update to Chapter 11 focuses on improving the visual presentation and content flow. Key changes include adding video callouts, integrating cross-references for videos, and refining the formatting of exercise callouts for better readability.
Chapter 19: AI for Good: The Chapter 19 content on AI for Good received updates including the addition of video callouts and end-of-section resources. Exercise callout blocks were also reorganized for improved visual presentation.

Let me know if you’d like a more detailed breakdown of any specific commit! - Chapter 12: Benchmarking AI: This update improves the visual presentation and organization of Chapter 12’s benchmarking content. It includes changes like adding video callouts, streamlining exercise sections, and correcting minor formatting issues. - Chapter 6: Data Engineering: Chapter 6 on Data Engineering was updated with video callouts and end-of-section resources for enhanced learning. Exercise callout blocks were also reorganized for improved visual clarity.

Let me know if you need help summarizing any other Git commit messages! - Chapter 3: DL Primer: This update includes adding video callouts within Chapter 3, enhancing the learning experience with visual elements. Additionally, it addresses a previous formatting issue with a “.callout” element. - Chapter 9: Efficient AI: This update adds video callouts to Chapter 9 on Efficient AI, along with resources at the end of each section. A previous error was also corrected involving the .callout format. - Chapter 7: AI Frameworks: This update improves the visual presentation of Chapter 7 by adding video callouts and end-of-section resources, while also refactoring exercise callout blocks for better aesthetics.

Let me know if you need anything else! - Chapter 2: ML Systems: This update to Chapter 2 enhances the visual appeal and user experience by adding video callouts, consolidating exercise callout blocks, and fixing a previous formatting issue. - Chapter 14: On-Device Learning: This update to Chapter 14 refines the presentation with video callouts for enhanced engagement and consolidated end-of-section resources. Exercise callout blocks were also reorganized for improved readability. - Chapter 13: ML Operations: The Chapter 13 content on ML Operations was updated to include video callouts and end-of-section resources. Exercise callout blocks were also reorganized for improved visual presentation. - Chapter 10: Model Optimizations: Chapter 10 on Model Optimizations was enhanced with video callouts and end-of-section resources for improved learning. The layout was also refined by folding all exercise callout blocks for better visual presentation. - Chapter 15: Security & Privacy: Chapter 15 on Security & Privacy was updated with added video callouts to enhance engagement and resources at the end of the section. The visual presentation was also improved by folding all exercise callout blocks for a cleaner look. - Chapter 16: Responsible AI: This update includes video callouts within Chapter 16 to enhance learning and provides additional resources at the end of the section for further exploration. A previous error with the .callout formatting was also corrected. - Chapter 18: Robust AI: Chapter 18 on Robust AI was updated with additional video callouts, end-of-section resources, and improved formatting for exercise callout blocks. The content also received enhancements with references, links, and expanded descriptions, including information about Bayesian Neural Networks (BNNs). - Chapter 17: Sustainable AI: This update improves the visual presentation of Chapter 17 on Sustainable AI by adding video callouts, integrating end-of-section resources, and restructuring the exercise callout blocks for better aesthetics. - Chapter 8: AI Training: This update focuses on visual improvements and content organization for Chapter 8’s AI Training section. Key changes include adding video callouts, restructuring exercise blocks for better readability, and fixing rendering issues with tables. - Chapter 5: AI Workflow: This update adds video callouts to Chapter 5’s AI Workflow and includes resources at the end of the section. A previous issue with the callout formatting was also fixed.

Let me know if you have any other Git commit messages you’d like summarized! - Generative Ai: The “coming soon” text for Generative AI features was added and refined in these commits.

This provides early users with an indication of what’s to come.

📅 June 01 at 01:31 PM

📖 Chapters

Chapter 19: AI for Good: This update fixes a broken Colab badge and improves the formatting of Chapter 19 content, including slides and exercises, ensuring they display correctly in PDF.

The commit also adds bullets to the “Coming Soon” section for better readability. - Chapter 12: Benchmarking AI: This update fixes a broken Colab badge and refines the presentation of Chapter 12 content. It includes formatting improvements for labs, exercises, and slides, ensuring better PDF rendering. - Chapter 6: Data Engineering: This update addresses several minor issues in the Chapter 6: Data Engineering content. Fixes include resolving a broken Colab badge, improving the “Coming Soon” section formatting, and correcting markdown issues for better readability. - Chapter 3: DL Primer: This update fixes a broken Colab badge and improves the “coming soon” section with bullet points. Additional formatting changes were made to ensure slides render correctly in PDF and enhance the overall presentation of labs, exercises, and slides. - Chapter 7: AI Frameworks: This update fixes a broken Colab badge and improves the formatting of Chapter 7 content, including slides and exercises, for better rendering in PDF. Additionally, it clarifies upcoming content with bullet points. - Chapter 11: AI Acceleration: Chapter 11 on AI Acceleration was updated with various formatting improvements and bug fixes. This includes resolving a broken Colab badge, standardizing note usage for slides, and enhancing the rendering of labs and exercises in PDF format. - Chapter 2: ML Systems: This update fixes rendering issues, improves Colab badge integration, and refines formatting for exercises, slides, and PDF output. Minor bullet point and “coming soon” section edits were also made. - Chapter 14: On-Device Learning: This update primarily focuses on fixing formatting issues and improving the visual presentation of Chapter 14. It addresses broken Colab badges, header inconsistencies, and slide rendering problems for better PDF compatibility. - Chapter 13: ML Operations: This update fixes a broken Colab badge from a previous commit and improves the “coming soon” section with bullet points. Additional formatting changes were made to ensure slides render correctly in PDF and enhance the overall presentation of labs, exercises, and slides. - Chapter 10: Model Optimizations: This update fixes a broken Colab badge and improves the presentation of Chapter 10 content. Key changes include using the @exr- format for Colab notebooks, formatting exercises and slides for better PDF rendering, and updating “coming soon” sections with bullet points. - Chapter 15: Security & Privacy: This update fixes issues with the Colab badge and formatting, ensures slides display correctly in PDFs, and improves the “coming soon” section with bullet points. Various formatting changes were also made to labs, exercises, and slides for better clarity and consistency. - Chapter 18: Robust AI: This update fixes several rendering and display issues in Chapter 18, including a broken Colab badge and formatting problems with slides and labs. It also standardizes note usage for better PDF output. - Chapter 17: Sustainable AI: This update fixes a broken Colab badge and improves the formatting of slides, labs, and exercises. It also clarifies upcoming content using bullet points instead of a general “coming soon” message. - Chapter 8: AI Training: This update fixes a broken Colab badge, standardizes notebook links with “(exr?)-”, and improves the formatting of slides and exercises for better PDF rendering. Additionally, the “coming soon” section now uses bullet points for readability. - Chapter 9: Efficient AI: This update focuses on improving the rendering and formatting of Chapter 9: Efficient AI. It addresses issues with rendering, corrects header formatting inconsistencies, and standardizes slide note usage for better PDF output. - Generative Ai: This update addresses rendering issues within the Generative AI section. The fixes ensure content displays correctly for users. - Chapter 16: Responsible AI: This update focuses on improving the visual presentation and readability of Chapter 16. It includes formatting changes to labs, exercises, and slides for better PDF rendering and clarifies the “coming soon” section with bullet points. - Chapter 5: AI Workflow: This update focuses on improving the presentation and formatting of Chapter 5’s content. It includes clearer bullet points for the “coming soon” section, ensures slides render correctly in PDF format, and refines the formatting of labs, exercises, and slide presentations. - Chapter 1: Introduction: The Introduction chapter now includes restored URL references for better context and navigation. Grammar and readability were also enhanced to improve the overall flow and clarity of the text.

📅 May 26 at 05:34 PM

📖 Chapters

Acknowledgements: The Acknowledgements section now includes added image logos for better visual representation. This initial draft serves as a starting point for recognizing contributors and resources.
Chapter 10: Model Optimizations: Chapter 10 was updated with numerous improvements, including fixes for broken links and citations, added video captions and exercises, and incorporation of co-lab badges. Additionally, stylistic changes and path link cleanups were implemented for a polished final product.
Chapter 18: Robust AI: The Chapter 18 on Robust AI was significantly updated with content about the importance of addressing safety and bias in AI, incorporating feedback from reviewers, and fixing numerous formatting, reference, and image issues. The chapter now includes a resources section for further exploration and learning objectives to guide readers.
Chapter 20: Conclusion: The conclusion for Chapter 20 was extensively revised, including updates to wording, grammar, formatting, and section headers. Additional improvements were made to address framework discussions and incorporate references and a cover image.
Chapter 3: DL Primer: Chapter 3 received significant updates including improved clarity and structure with the addition of section headers and captions, as well as enhancements to existing content like the Data Diversity and Quality section. Furthermore, collaborative elements were incorporated with the addition of videos and Colab badges.
Chapter 14: On-Device Learning: This update to Chapter 14 enhances the readability and usability of On-Device Learning content with grammar fixes, punctuation corrections, clearer links, and added captions for tables and videos. Furthermore, it incorporates collaborative learning exercises, additional slides, and video content.
Chapter 17: Sustainable AI: This update focuses on improving clarity and consistency within Chapter 17. It includes grammatical edits, stylistic changes, fixes for broken links and references, and the addition of section headers for easier navigation.
Chapter 9: Efficient AI: Chapter 9 on Efficient AI was updated with several improvements, including formatting fixes, image reference corrections, added section headers for cross-referencing, and captions for tables. The chapter also includes new slides and stylistic changes.
Chapter 6: Data Engineering: Chapter 6 on Data Engineering was significantly updated with new slides, exercises, and content. Numerous improvements were also made including fixing references, correcting typos, and enhancing the overall style and readability of the chapter.
Chapter 8: AI Training: This update for Chapter 8 focuses on improving readability and visual presentation. It includes grammar and punctuation fixes, added figure and table captions, incorporated short video captions, and updated the code to enable PDF builds.
Chapter 7: AI Frameworks: This update significantly improves the clarity and accuracy of Chapter 7 on AI Frameworks. Fixes include addressing broken links, correcting references, adding captions to tables, and refining grammar and punctuation for better readability.
Chapter 13: ML Operations: Chapter 13 on ML Operations was significantly updated with improvements to slide links, figure captions, and table formatting. Additional content includes embedded videos and a clearer structure with section headers for easy navigation.
Chapter 15: Security & Privacy: Chapter 15 on Security & Privacy was updated with several improvements, including fixing broken slide links, adding section headers for easier navigation, and incorporating captions for tables and videos. The chapter also received styling refinements and bug fixes related to PDF builds and file paths.
Chapter 5: AI Workflow: This update primarily focuses on improving the readability and accuracy of Chapter 5. It includes fixes for broken slide links, grammatical errors, table captions, and stylistic changes, along with structural improvements like adding section headers for cross-referencing.
Chapter 19: AI for Good: The main updates for Chapter 19 involve improving readability and consistency with grammar fixes, punctuation corrections, and stylistic changes like adding section headers and captions for videos. Additionally, technical improvements were made to enable PDF builds and address issues with SVG images.
Chapter 12: Benchmarking AI: Chapter 12 on Benchmarking AI has been significantly improved with grammar and stylistic edits, added section headers for easier navigation, and fixes to enable PDF builds. Additionally, collaboration badges have been integrated into the chapter.
Chapter 11: AI Acceleration: Chapter 11 on AI Acceleration received significant updates including fixes for broken links, improved figure captions and references, grammar and punctuation edits, and the addition of short video captions. The chapter also now features updated content with collapsible sections and integrates Colab badges for enhanced interactivity.
Chapter 2: ML Systems: Chapter 2, “ML Systems”, was updated with improved clarity and structure through grammar checks, caption additions for figures and tables, and stylistic refinements. The chapter now focuses solely on ML systems at large, removing the previously included “Embedded Systems” section.
Chapter 16: Responsible AI: This update focuses on refining Chapter 16’s content and presentation. Key changes include adding section headers for easier navigation, fixing broken links, correcting grammar, and improving visual styling with video captions and formatting adjustments.
Generative Ai: This update focused on improving readability and organization within the Generative AI documentation. It added section headers for easier cross-referencing and updated the “Coming soon” text for a more consistent style.
Chapter 1: Introduction: The introduction chapter was enhanced with structural improvements like section headers, a reference section, and clearer relative path links. Visual elements were also added, including a cover image and illustrations from Mark’s article.
Dsp Spectral Features Block: Minor punctuation fixes were made to improve readability, specifically correcting the use of “vs.” instead of “:”.

Let me know if you have other commit messages you’d like me to summarize! - Lab: Arduino Image Classification: This update makes punctuation fixes to the “image_classification.qmd” file in the “contents/image_classification” directory.

Let me know if you’d like me to elaborate on any specific commit message! - Kws Feature Eng: Minor punctuation corrections were made in the Kws Feature Eng document to improve readability.

Let me know if you’d like me to summarize any other commit messages! - Motion Classify Ad: This commit made punctuation corrections to the Motion Classify Ad documentation within the motion_classify_ad.qmd file, ensuring clarity and consistency in the text.

Let me know if you have any other Git commit messages you’d like summarized! - Niclav Sys: This commit addresses punctuation inconsistencies in the Niclav Sys documentation by correcting “: vs. :”. - Embedded Ml: The Embedded ML documentation was updated with edits to chapters 1 through 4, ensuring they remain accessible and clear to readers.

This change also set collapse=false for these sections, potentially making them always visible instead of collapsed by default. - Embedded Sys: The Embedded Sys documentation (contents/embedded_sys/embedded_sys.qmd) was updated with additional content, including new slides for chapters 1 through 4. These changes were accompanied by adjustments to ensure all sections remain visible and accessible.

Let me know if you’d like me to elaborate on any specific commit message!

📅 March 21 at 12:26 PM

📖 Chapters

Chapter 6: Data Engineering: Chapter 6 on Data Engineering was updated with clear exercise callouts and improved organization. Additionally, a “Resources” section was added to all QMDs for potential future content.
Chapter 19: AI for Good: This update enhances Chapter 19 by organizing resources with introductory text and collapsible sections. Additionally, slides have been moved to the end of the page for improved readability and flow.
Chapter 12: Benchmarking AI: This update focuses on organization and structure within Chapter 12. It introduces collapsible resource sections with introductory text, moves slides to the end of each page, and standardizes the addition of an empty “Resources” section to all QMD files.
Chapter 3: DL Primer: Chapter 3’s DL Primer was enhanced with more slides, resources now include introductory text and collapsible sections, and an empty “Resources” section has been added to all QMD files.

Let me know if you need any further assistance! - Chapter 9: Efficient AI: Chapter 9 on Efficient AI received several improvements. Key changes include adding more slides, introducing introductory text and collapsible sections for resources within the chapter, and standardizing a “Resources” section across all QMD files. - Embedded Ml: This update enhances the Embedded ML content by adding introductory text and collapse functionality to resources, incorporating more slides, restructuring slide placement, and introducing a standardized “Resources” section at the end of QMD files. - Embedded Sys: This update enhances the Embedded Sys guide by adding introductory text and collapse functionality to resources, incorporating more slides, and restructuring them for better organization. It also standardizes QMDs with an added “Resources” section at the end. - Chapter 7: AI Frameworks: The Chapter 7 content on AI Frameworks was updated to include more slides and integrate interactive Colab badges within the Resources section. This update also involved restructuring slide placement and adding introductory text for each part of the resources. - Chapter 11: AI Acceleration: Chapter 11 now features improved organization with an introductory text for each resource section, allowing for easy navigation and content collapsing. Additionally, an empty “Resources” section has been added to all QMD files, providing a consistent structure across chapters. - Chapter 14: On-Device Learning: Chapter 14 on On-Device Learning was updated with additional slides, reorganized content by moving slides to the end of pages, and enhanced the “Resources” section with introductory text and collapsible features.

This summary highlights the most significant changes: increased slide count, content restructuring, and improved resource organization. - Chapter 13: ML Operations: This update enhances Chapter 13 by adding more slides, restructuring content to place slides at the end of pages, and introducing a new “Resources” section with collapsible summaries for each part. - Chapter 10: Model Optimizations: This update enhances Chapter 10 by adding introductory text and collapsible sections to its Resources, moving slides to the end of pages, and standardizing resource sections across all QMD files. These changes improve organization and navigation for users. - Chapter 15: Security & Privacy: Chapter 15 on Security & Privacy was enhanced by adding more slides, organizing them at the end of the page, and introducing a new “Resources” section with introductory text for each part. This update improves navigation and provides clearer organization for content related to security and privacy. - Chapter 16: Responsible AI: Chapter 16 on Responsible AI now features an organized “Resources” section with introductory text for each part, collapsible by default. The slides have been moved to the end of the page to improve readability and flow. - Chapter 17: Sustainable AI: Chapter 17 now features organized resources with introductory text for each part, allowing users to easily navigate them. Additionally, slides have been moved to the end of the page, improving content flow and readability. - Chapter 8: AI Training: Chapter 8 on AI Training was enhanced with more slides and an organized “Resources” section. This section now includes introductory text for each part, collapsible features for better navigation, and is consistently placed at the end of all QMD files. - Chapter 5: AI Workflow: This update focuses on improving organization and readability within Chapter 5. It introduces collapsible sections for resources with introductory text, moves slides to the end of the page, and adds a standard “Resources” section to all QMD files.

📅 March 12 at 11:50 PM

📖 Chapters

Chapter 11: AI Acceleration: Chapter 11 has been streamlined by removing unnecessary figures and Mermaid diagrams. Additionally, scripts for checking (non-)ASCII characters have been implemented along with relevant fixes to ensure code compatibility.
Niclav Sys: This update corrects broken links within the content and introduces new scripts for checking ASCII compliance, along with necessary fixes to ensure proper functionality.
Embedded Ml: The Embedded ML documentation was updated with a nested example, new styling features including arrows and custom callouts, and additional slides for improved clarity and comprehensiveness. Debug code was also removed for cleaner presentation.
Chapter 7: AI Frameworks: The Chapter 7 content on AI Frameworks has been significantly enhanced with the addition of Colab notebooks for interactive learning, more slides for visual explanations, and styling improvements.

Additionally, non-ASCII character handling issues were addressed to ensure proper rendering across different systems. - Chapter 6: Data Engineering: The Data Engineering chapter was significantly updated with interactive Colab notebooks, additional slides, and a new web scraping exercise integrated into both the subsection and the Exercises section. Other improvements include fixing previous notes, adding scripts for checking ASCII compatibility, and organizing content across six chapters. - Chapter 19: AI for Good: Chapter 19 on AI for Good has been enhanced with additional slides to provide a more comprehensive overview. The chapter also includes improved scripts and fixes for checking ASCII characters in various files. - Chapter 12: Benchmarking AI: Chapter 12 on Benchmarking AI received several updates, including expanded content with added slides and corrections to previous notes. Additionally, new scripts were implemented for checking ASCII compliance and other related fixes.

Let me know if you have any other text snippets you’d like me to summarize! - Chapter 3: DL Primer: The Chapter 3 Git commit adds more slides to the DL Primer content. Additionally, it includes scripts and fixes for checking ASCII compliance in the text. - Embedded Sys: The embedded_sys.qmd file received new slides content and saw improvements with the addition of scripts to check for (non-)ASCII characters, along with related bug fixes. - Chapter 14: On-Device Learning: Chapter 14 on On-Device Learning has been expanded with additional slides. Additionally, scripts for checking ASCII compliance and related fixes have been implemented. - Chapter 13: ML Operations: Chapter 13 on ML Operations was updated with additional slides and corrections to previous content. The chapter also includes new scripts for checking (non-)ASCII characters, along with necessary fixes. - Chapter 15: Security & Privacy: Chapter 15 on Security & Privacy was expanded with additional slides and revisions were made to correct inaccuracies from the previous week’s notes. The chapter now comprises six complete chapters. - Chapter 16: Responsible AI: Chapter 16 on Responsible AI was enhanced with additional slides to provide a more comprehensive overview of the topic. Minor styling adjustments were also made to ensure proper rendering. - Chapter 17: Sustainable AI: Chapter 17 on Sustainable AI has been expanded with additional slides for a more comprehensive overview. Additionally, scripts and fixes related to checking for ASCII characters have been implemented. - Chapter 8: AI Training: Chapter 8, “AI Training,” was enhanced with additional slides to provide a more comprehensive overview. Bug fixes were implemented, including improvements to non-ASCII character handling and rendering styles for a polished presentation. - Chapter 5: AI Workflow: Chapter 5 on AI Workflow was expanded with additional slides and corrected content from previous weeks. New scripts were also added to check for (non-)ASCII characters, along with accompanying fixes. - Chapter 10: Model Optimizations: This update focuses on improving the accuracy and presentation of Chapter 10: Model Optimizations. It includes fixes to previous notes, adds scripts to check for non-ASCII characters, and enhances the styling for successful rendering. - Chapter 9: Efficient AI: This update includes the addition of scripts to check for non-ASCII characters in the “Efficient AI” chapter, along with necessary fixes to address any issues found.

📅 February 03 at 09:53 AM

📖 Chapters

Chapter 12: Benchmarking AI: This commit focuses on improving the visual presentation of the Benchmarking section in Chapter 12. It removes unnecessary list items and ensures consistent styling for improved readability.
Chapter 14: On-Device Learning: The Chapter 14 content on On-Device Learning was updated to fix rendering issues with itemized lists. This ensures the information is presented clearly and correctly for readers.

Let me know if you have any other Git commit messages you’d like summarized! - Chapter 13: ML Operations: The MCU example in the Chapter 13 content about Machine Learning Operations (MLOps) was updated to reflect a smartwatch scenario, and a relevant citation was added for further reading. - Chapter 15: Security & Privacy: Chapter 15’s content on privacy and security received updates to improve user experience. Video rendering issues were fixed, and the sections on GDPR and CCPA were enhanced with clearer hyperlinking and a more concise summary of CCPA regulations. - Chapter 11: AI Acceleration: This update addresses an issue in Chapter 11 related to video rendering acceleration, ensuring proper functionality for this feature.

Let me know if you’d like me to elaborate on any specific commit message! 😊 - Chapter 3: DL Primer: The DL Primer chapter now has corrected video rendering to ensure smooth playback and viewing experience. - Chapter 19: AI for Good: Chapter 19, “AI for Good,” was updated to fix issues with video rendering and resolve improperly shortened YouTube URLs. These changes ensure smoother content playback and accurate linking within the chapter. - Chapter 17: Sustainable AI: Formatting was improved by ensuring consistent spacing for list items within Chapter 17 on Sustainable AI. Additionally, a citation was added to reference an OECD blueprint paper relevant to the content.

📅 February 02 at 06:17 PM

📖 Chapters

Chapter 19: AI for Good: Chapter 19, “AI for Good,” was updated to fix broken image links and integrate content from branch ‘81-figure-references/part-2’. All bibliographic references were also automatically updated.

Let me know if you’d like a more detailed breakdown of any specific commit! - Chapter 11: AI Acceleration: Chapter 11, “AI Acceleration,” has been updated with several important fixes. This includes resolving broken image links and bibliographic references, as well as incorporating changes from the ‘81-figure-references/part-2’ branch for improved accuracy and clarity. - Chapter 13: ML Operations: Several issues with broken image references and links were fixed in Chapter 13, including rendering issues with Figure 14.3. Additionally, all BibTeX references were updated automatically for consistency. - Chapter 15: Security & Privacy: This update fixes several issues with image and video references in Chapter 15, ensuring they display correctly. It also includes updated BibTeX references for improved accuracy. - Chapter 17: Sustainable AI: Chapter 17 on Sustainable AI has been updated to fix broken image links and references, incorporate changes from branch ‘81-figure-references/part-2’, and automatically update all BibTeX references.

This ensures accuracy and readability for this important chapter. - Chapter 6: Data Engineering: This update enhances Chapter 6 on Data Engineering with a new web scraping Colab exercise and improved image quality by converting PNGs to JPGs. Additionally, all BibTeX references have been automatically updated for accuracy. - Chapter 16: Responsible AI: Chapter 16 on Responsible AI was updated with several improvements. This includes fixing an issue with citations using the “@” symbol and automating the update of all BibTeX references for accuracy. - Chapter 12: Benchmarking AI: This update to Chapter 12, “Benchmarking AI,” focuses on fixing reference rendering issues and updating all BibTeX entries for improved accuracy and consistency. This ensures smoother reading and proper attribution throughout the chapter. - Chapter 10: Model Optimizations: This update focuses on refining Chapter 10 content related to model optimizations. It addresses missing references and corrects an incomplete illustration, while also ensuring all BibTeX references are up-to-date. - Chapter 14: On-Device Learning: This update to Chapter 14 on On-Device Learning primarily focuses on formatting improvements and content refinement. A few hyperlinked images were removed due to broken sources, and the chapter’s structure was adjusted for clarity. - Embedded Sys: This commit streamlines the documentation process for Embedded Sys by automating the updating of all BibTeX references within the embedded_sys.qmd file. This ensures accuracy and consistency in citing sources. - Chapter 8: AI Training: The AI Training chapter now features automated updates for all BibTeX references, ensuring accuracy and consistency.

This change simplifies maintenance and keeps the references current. - Embedded Ml: The Embedded ML documentation now utilizes PNG images instead of other formats, enhancing visual clarity for users.

Let me know if you’d like me to elaborate on any specific commit or aspect of the changes! - Chapter 3: DL Primer: The Chapter 3 “DL Primer” was updated to use PNG images instead of SVGs for PDF builds, improving rendering quality in PDFs.

📅 January 02 at 12:08 PM

📖 Chapters

Niclav Sys: A typo was corrected in the “Installing the OpenMV IDE” chapter of Niclav Sys documentation. This ensures accuracy and clarity for users following the installation instructions.
Chapter 7: AI Frameworks: Chapter 7’s content on AI frameworks was improved with fixes to a callout-tip error and minor syntax issues, ensuring accuracy and readability.

2023 Updates

📅 December 19 at 09:31 AM

📖 Chapters

Chapter 10: Model Optimizations: Chapter 10 on model optimizations received significant updates, including the addition of visual figures to illustrate concepts and numerous fixes for broken references and formatting errors. These improvements enhance clarity and understanding of the chapter’s content.

📅 December 18 at 11:08 AM

📖 Chapters

Chapter 12: Benchmarking AI: The Chapter 12 content on AI Benchmarking was moved to the “benchmarks/leaderboards” section for better organization. Additionally, a fix was implemented to ensure correct reference display when multiple references are present within a commit message.
Chapter 17: Sustainable AI: Chapter 17 on Sustainable AI was updated to include content about benchmarks and leaderboards, along with revisions to wording, citations, and formatting for clarity and accuracy. Minor fixes addressed issues with reference separation and markdown rendering across platforms.
Chapter 10: Model Optimizations: This update addresses a markdown formatting issue specifically affecting Windows users within Chapter 10’s content on model optimizations.

Let me know if you have any other commit messages you’d like summarized! - Chapter 7: AI Frameworks: This commit updates the Colab notebooks for Chapter 7: AI Frameworks, incorporating contributions from Marcelo. These updates likely enhance the learning experience by providing more hands-on examples and interactive elements related to various AI frameworks.

Let me know if you’d like me to elaborate on any specific aspect of the changes!

📅 December 13 at 12:41 PM

📖 Chapters

Chapter 7: AI Frameworks: The Colab notebooks for Chapter 7: AI Frameworks were updated, incorporating contributions from Marcelo. This update likely includes improvements and refinements to the code examples and explanations within the Colab environment.
Chapter 9: Efficient AI: A broken URL link was fixed in Chapter 9’s content on Efficient AI. This ensures that readers can access the intended resources without encountering errors.
Chapter 12: Benchmarking AI: The commit messages indicate that the primary update for Chapter 12 is a fix to the spacing of references, ensuring proper formatting within the benchmarking section.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 8: AI Training: The path to the training content was updated in Chapter 8: AI Training.

This update likely ensures the correct location for accessing training resources within the project’s documentation. - Chapter 10: Model Optimizations: This update addresses a missing reference to an attention paper within the “optimizations.qmd” file, ensuring accurate citations for relevant research.

Let me know if you’d like me to elaborate on any specific commit message!

📅 December 12 at 04:10 PM

📖 Chapters

Chapter 12: Benchmarking AI: Minor formatting and consistency improvements were made to Chapter 12, including fixing reference spacing and standardizing “tinyML” capitalization.
Chapter 8: AI Training: This update streamlines AI training content by removing the duplicate activation function primer and consolidating the computation graph into the training section. It refines the structure for better clarity and efficiency.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 10: Model Optimizations: This update focuses on refining citations and terminology within Chapter 10. It ensures consistency by using square brackets for references and standardizing “tinyML” throughout the chapter.

Let me know if you’d like a more detailed summary of any specific commit! - Chapter 3: DL Primer: The DL primer’s activation function was removed, and the computation graph logic was moved into the training section. This restructuring likely streamlines the presentation of how models are trained in the DL Primer chapter.

Let me know if you have any other Git commit messages you’d like summarized! - Generative Ai: Please provide the commit messages for contents/generative_ai/generative_ai.qmd so I can generate a brief summary of the updates. - Chapter 18: Robust AI: This commit focuses on cleaning up the content for Chapter 18: Robust AI, ensuring clarity and organization within the “robust_ai.qmd” file.

Let me know if you’d like me to elaborate on any specific changes mentioned in the commit messages! - Chapter 6: Data Engineering: This commit brings consistency to the “Chapter 6: Data Engineering” content by changing all instances of “tinyML” to “TinyML”.

Let me know if you’d like me to elaborate on any specific changes! - Embedded Ml: Please provide the Git commit messages for me to summarize. - Embedded Sys: This commit improves consistency by changing “tinyML” to “TinyML” throughout the embedded_sys.qmd file. - Chapter 11: AI Acceleration: This update ensures consistency in terminology by changing “tinyML” to “TinyML” throughout Chapter 11 on AI Acceleration.

There were no substantial functional changes, only stylistic revisions. - Chapter 14: On-Device Learning: This update to Chapter 14 on On-Device Learning refines the wording for clarity and accuracy, ensuring the content is more easily understood. No significant structural or conceptual changes were made.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 7: AI Frameworks: This update ensures consistency in naming by changing “tinyML” to “TinyML” across all mentions within the Chapter 7 content on AI Frameworks.

Let me know if you’d like me to elaborate on any specific aspect of the commit messages! - Lab: Arduino Image Classification: This commit ensures consistency in the project by updating instances of “tinyML” to “TinyML”. - Kws Nicla: This update ensures consistency in naming by changing “tinyML” to “TinyML” across all instances within the Kws Nicla documentation.

Let me know if you’d like me to elaborate on any specific commit message! - Chapter 16: Responsible AI: This update ensures consistency by changing all instances of “tinyML” to “TinyML” throughout Chapter 16 on Responsible AI.

Let me know if you’d like me to elaborate on any specific commit or aspect of the chapter! - Chapter 5: AI Workflow: The “AI Workflow” chapter’s content was updated for consistency, renaming “tinyML” to “TinyML” across all instances.

📅 December 11 at 04:51 PM

📖 Chapters

Chapter 3: DL Primer: The Chapter 3 DL Primer was reorganized significantly, including a new folder structure for better organization and separate reference files for each chapter. Additional changes involved moving computation graph implementation to the training section and removing the activation function from the DL primer.
Chapter 8: AI Training: Chapter 8 on AI Training was reorganized with a new folder structure for better navigation and management. The training section now includes its own computation graph and references, while image files are categorized by type within dedicated subfolders.
Generative Ai: The Generative AI content was reorganized with a new folder structure, including dedicated reference files for each chapter and image subfolders categorized by file type. This restructuring aims to improve clarity and organization within the content.
Chapter 18: Robust AI: Chapter 18, “Robust AI”, was significantly reorganized with a new folder structure and distributed reference files for each chapter. This update improves organization and clarity within the content.

Let me know if you need help summarizing other commit messages! - Chapter 12: Benchmarking AI: Chapter 12 was reorganized significantly with a new folder structure, including subfolders for different image types. Additionally, consistency was improved by updating “tinyML” to “TinyML” and distributing references into individual chapter files. - Chapter 6: Data Engineering: This update significantly reorganized Chapter 6’s content, creating separate reference files for each chapter and structuring images into type-specific subfolders. Additionally, minor stylistic changes were made to ensure consistency in terminology like “tinyML”. - Embedded Ml: The Embedded ML documentation was reorganized with a new folder structure and subfolders within the “images” directory, categorized by file type. Additionally, references were distributed to individual chapter files for better organization. - Embedded Sys: This update significantly reorganized the Embedded Sys documentation by creating a structured folder system and separating references for each chapter. Additionally, it standardized terminology and improved image organization. - Chapter 11: AI Acceleration: This update to Chapter 11 focuses on improving organization and referencing. It includes a major restructuring of files, the use of dedicated reference files for each chapter, and updated content on machine learning acceleration techniques. - Chapter 14: On-Device Learning: Chapter 14 now features a reorganized file structure with dedicated subfolders for different image types and individual reference files for each chapter. This update improves clarity and organization within the book content. - Chapter 7: AI Frameworks: This update to Chapter 7 reorganizes the framework content, including updating terminology, fixing broken links, and distributing references by chapter. A new folder structure with subfolders for image types further improves organization. - Lab: Arduino Image Classification: This update significantly restructured the Lab: Arduino Image Classification repository. It includes a consistent naming convention for “TinyML”, distributed references by chapter, organized image files by type, and a comprehensive reorganization of the entire file structure. - Kws Nicla: The Kws Nicla documentation was significantly reorganized, including creating folders for different image types and separating references by chapter. This restructuring aims to improve clarity and navigation within the documentation. - Chapter 10: Model Optimizations: Chapter 10 received several formatting and structural improvements. This includes standardizing terminology, removing duplicate content, and reorganizing files into a more logical folder structure for better navigation. - Chapter 16: Responsible AI: The main updates for Chapter 16 include a significant restructuring of files and folders, improved consistency in terminology by changing “tinyML” to “TinyML”, and a move towards distributing references within each chapter’s folder. - Chapter 5: AI Workflow: This update significantly reorganized Chapter 5’s content, creating a more structured and navigable experience. It also standardized terminology (“tinyML” instead of “TinyML”), distributed references to chapter-specific files, and organized images into subfolders based on file type. - Chapter 9: Efficient AI: Chapter 9, “Efficient AI”, received significant updates including visual fixes, added references to relevant datasets and ResNet architectures, and a major reorganization of its files into a clearer folder structure. This refactoring improves readability, accuracy, and overall organization within the chapter. - Chapter 19: AI for Good: Chapter 19 now has its own dedicated references file, and all images are organized into subfolders based on their type. The chapter’s files have also been reorganized into a more logical folder structure for improved clarity and navigation. - Dsp Spectral Features Block: This update significantly reorganized the Dsp Spectral Features Block, including creating separate reference files for each chapter and categorizing images by type. The files were also restructured into a more logical folder system for improved organization and navigation. - Kws Feature Eng: The Kws Feature Eng documentation was reorganized with a new folder structure, separating files by type and distributing references to individual chapters. This improves organization and navigation within the document. - Motion Classify Ad: The Motion Classify Ad was reorganized with a new folder structure, including separate reference files for each chapter and categorized image folders. This improves organization and clarity within the project. - Niclav Sys: Niclav Sys was reorganized with a new file structure, including separate reference files for each chapter and image subfolders categorized by file type. This significantly improves organization and navigation within the project.

Let me know if you need more details from any specific commit! - Object Detection Fomo: This commit brings major structural changes to the Object Detection Fomo documentation. It introduces separate reference files for each chapter, organizes images by type within dedicated subfolders, and implements a comprehensive folder structure for improved file management. - Chapter 13: ML Operations: Chapter 13’s content was reorganized with a new folder structure for better navigation, and image files were categorized into subfolders by type. Additionally, each chapter now has its own dedicated references file.

Let me know if you have any other text you’d like summarized! - Chapter 15: Security & Privacy: Chapter 15 on Security & Privacy was reorganized with a new folder structure for better organization. This includes separating references by chapter and categorizing images within a dedicated ‘images’ folder. - Chapter 17: Sustainable AI: Chapter 17 on Sustainable AI now features separate reference files for each chapter and an organized folder structure within the “images” directory. This improves navigation and clarity by grouping related content and resources.

📅 December 10 at 08:16 PM

📖 Chapters

Chapter 8: AI Training: Chapter 8 was reorganized with a new folder structure for better navigation, and image files were categorized into subfolders based on their type. References within the text were also corrected to ensure proper punctuation.
Chapter 19: AI for Good: The Chapter 19 content has been reorganized with a new folder structure for better organization and easier navigation. Images have also been sorted into subfolders based on their file type.
Chapter 12: Benchmarking AI: The chapter on Benchmarking AI has been significantly reorganized by creating a more structured folder system within the “images” directory, categorized by file type. This improves organization and navigation for the content related to benchmarking AI models.
Chapter 6: Data Engineering: The Chapter 6 content has been reorganized with a new folder structure for improved navigation and clarity. Images have also been categorized into subfolders based on their file type.

Let me know if you’d like me to elaborate on any specific change or commit message! - Chapter 3: DL Primer: The Chapter 3 “DL Primer” content was reorganized for better clarity and navigation. This includes creating subfolders within the “images/” directory based on file type and restructuring all files into a logical folder system. - Dsp Spectral Features Block: This commit reorganized the DSP Spectral Features Block, creating a more structured directory layout with subfolders in the “images” directory based on file type. This significantly improves organization and readability within the project. - Chapter 9: Efficient AI: Chapter 9’s content, “Efficient AI,” has been reorganized with a new folder structure. This includes creating subfolders within the “images” directory based on file type for improved organization and navigation.

Let me know if you have any other text you’d like summarized! - Embedded Ml: The Embedded ML documentation now features a reorganized file structure with subfolders in the “images” directory categorized by file type. This restructuring aims to improve clarity and organization within the documentation. - Embedded Sys: The Embedded Systems documentation now features a reorganized file structure with subfolders within the “images” directory categorized by file type. This restructure improves navigation and organization for better usability.

Let me know if you have any other Git commit messages you’d like summarized! - Chapter 7: AI Frameworks: The Chapter 7 content on AI Frameworks was reorganized significantly. Files were moved into a clear folder structure based on file type, improving organization and navigation within the chapter. - Generative Ai: The contents/generative_ai/generative_ai.qmd directory was restructured with a new folder system to better organize files based on their type, including subfolders within the images folder. This reorganization aims to improve clarity and navigation within the project’s generative AI content. - Chapter 11: AI Acceleration: The “Chapter 11: AI Acceleration” content was reorganized by creating subfolders within the “images/” directory to categorize files by type and restructuring the overall file layout for better organization. - Lab: Arduino Image Classification: This commit introduces a more organized file structure for the image classification lab by creating subfolders within “images/” based on file type. This reorganization significantly improves clarity and makes it easier to navigate and manage the project’s files. - Kws Feature Eng: The Kws Feature Eng repository underwent a major restructuring, with the creation of subfolders within the “images” directory based on file type and a comprehensive reorganization of all files into a more logical folder structure. This change aims to improve organization and navigation within the project. - Kws Nicla: The kws_nicla documentation was reorganized with a new folder structure for better organization. Files were categorized by type, and placed within subfolders under “images/”.

Let me know if you need further details from any specific commit! - Motion Classify Ad: The Motion Classify Ad project underwent a major reorganization. Images were organized into subfolders based on file type, and the overall file structure was significantly improved for better organization and clarity.

Let me know if you’d like me to elaborate on any specific changes! - Niclav Sys: Niclav Sys’s QMD content was reorganized with a new folder structure. The “images/” directory now contains subfolders organized by file type, and all files have been restructured for improved clarity. - Object Detection Fomo: The codebase for Object Detection Fomo was reorganized by creating subfolders within “images/” based on file type and restructuring all files into a more organized folder structure. This improves project navigation and maintainability. - Chapter 14: On-Device Learning: The Chapter 14 content on On-Device Learning has been reorganized with a new folder structure to improve clarity and navigation. Files within the images/ directory are now organized by filetype for easier access.

Let me know if you’d like me to elaborate on any specific changes! - Chapter 13: ML Operations: Chapter 13 now features a more organized file structure with subfolders within “images/” categorized by file type. This reorganization aims to improve clarity and navigation within the chapter’s content. - Chapter 10: Model Optimizations: Chapter 10 now features a reorganized file structure with subfolders within the “images/” directory categorized by file type. This reorganization significantly improves clarity and navigability within the chapter’s content. - Chapter 15: Security & Privacy: Chapter 15’s content was reorganized by creating subfolders within the “images” directory based on file type and restructuring all files into a clear folder structure. This improves organization and navigation for easier access to specific resources within the chapter. - Chapter 16: Responsible AI: Chapter 16’s content was reorganized by creating subfolders within “images/” based on file type and restructuring all files into a clearer folder hierarchy. This improves organization and navigation within the chapter. - Chapter 17: Sustainable AI: Chapter 17’s content was reorganized for improved clarity and navigation by creating subfolders within the “images” directory based on file type and restructuring all files into a more logical folder hierarchy. This change enhances organization and makes it easier to find specific images and content. - Chapter 5: AI Workflow: The Chapter 5 content was reorganized significantly, including creating subfolders within the “images” directory to organize files by type and restructuring all files into a more logical folder structure. This improves navigation and clarity for readers. - Chapter 18: Robust AI: Chapter 18’s content on Robust AI was reorganized by moving its files into a clear folder structure for better organization and navigation.

Let me know if you need help summarizing any other Git commit messages! 😊