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Documentation updates across the codebase: Root documentation: - README.md: Updated references from book/ to site/ - CONTRIBUTING.md: Updated build and workflow instructions - .shared-ai-rules.md: Updated AI assistant rules for new structure GitHub configuration: - Issue templates updated for new module locations - Workflow references updated from book/ to site/ docs/ updates: - STUDENT_QUICKSTART.md: New paths and structure - module-rules.md: Updated module development guidelines - NBGrader documentation: Updated for module restructuring - Archive documentation: Updated references Module documentation: - modules/17_memoization/README.md: Updated after reordering All documentation now correctly references: - site/ instead of book/ - modules/XX_name/ instead of modules/source/
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TinyTorch: Build ML Systems from Scratch
Don't just import it. Build it.
A Comprehensive Course in Machine Learning Systems Engineering
Prof. Vijay Janapa Reddi Harvard University
2025 Edition
About This Book
This book provides a comprehensive, hands-on introduction to building machine learning systems from scratch. Rather than treating ML frameworks as black boxes, you'll implement every component yourself—from tensors and gradients to optimizers and attention mechanisms—gaining deep understanding of how modern ML systems actually work.
Course Philosophy
Build → Profile → Optimize
You'll implement each system component, measure its performance characteristics, and understand the engineering trade-offs that shape production ML systems. This approach transforms you from a framework user into a systems engineer who can debug, optimize, and architect ML solutions at scale.
Three-Tier Learning Pathway
Foundation Tier (Modules 01-07): Build mathematical infrastructure Architecture Tier (Modules 08-13): Implement modern AI architectures Optimization Tier (Modules 14-20): Deploy production systems
Course Website
For the latest updates, interactive exercises, and community resources, visit:
https://www.mlsysbook.ai/tinytorch
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
© 2025 Vijay Janapa Reddi. All rights reserved.