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v0.2.0: Scaling Beyond TinyML

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@profvjreddi profvjreddi released this 08 Oct 23:05
· 6248 commits to dev since this release
v0.2.0
2b3e0cc

Actual Release Date: June 20, 2024

This major release marks a pivotal transformation from TinyML-focused curriculum to comprehensive machine learning systems education. The scope expands far beyond embedded AI while preserving foundational principles, reflecting that ML systems principles are universal across deployment scales.

🎯 Key Highlights

📖 Content Expansion (54 files, +9 from v0.1.0)

  • Broadened Scope: Evolution from TinyML-specific to full-spectrum ML systems
  • Robust AI Chapter: New comprehensive chapter on fault-tolerant and resilient systems
  • Enhanced Labs: Expanded hardware support with Seeed XIAO ESP32S3
  • Shared Lab Content: Reusable modules across different hardware platforms
  • Getting Started Guides: Improved onboarding for students and educators

🛠️ Infrastructure Improvements

  • Build System: Enhanced reliability across HTML, PDF, and EPUB formats
  • Navigation: Added GitHub stars counter and improved banner system
  • Asset Management: Better organization of figures and media files
  • Documentation: Expanded getting started and setup guides

🎓 Expert Contributions

  • Marcelo Rovai: Extensive lab updates and hardware platform support
  • Community Contributors: Growing network of educators and practitioners
  • Hardware Partners: Integration with Seeed Studio and other vendors

📊 Major Changes (932 commits)

  • Content Files: 45 → 54 files (+20% growth)
  • Hardware Platforms: Added Seeed XIAO ESP32S3 support
  • Shared Labs: New reusable lab components
  • Infrastructure: Numerous build and deployment improvements
  • Bug Fixes: 100+ fixes for references, figures, and formatting

🔬 Educational Impact

This release positions the textbook as a comprehensive ML systems resource:

  • Comprehensive Systems Thinking: Beyond individual algorithms to full systems
  • Cross-Platform Expertise: From embedded devices to cloud-scale deployments
  • Practical Skills: Real-world engineering and operations knowledge
  • Industry Relevance: Preparation for production ML engineering roles

📋 Release Information

  • Release Date: June 20, 2024
  • Development Period: December 2023 - June 2024 (6 months)
  • Previous Version: v0.1.0
  • Commits: 932 improvements and additions

🔗 Quick Links

🏗️ Technical Details

  • Build Platform: Quarto with enhanced workflows
  • Formats: HTML, PDF, EPUB
  • New Features: Improved navigation, star counter, shared labs
  • Performance: Faster builds and better reliability

This release represents a fundamental shift in scope, establishing MLSysBook as the definitive resource for ML systems education across computing disciplines, from embedded devices to cloud-scale deployments.

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