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Reorganized Jupyter Book navigation from scattered sections to coherent ML systems progression: 🏗️ Foundation Tier (01-07): Core systems building blocks - Tensor, Activations, Layers, Losses, Autograd, Optimizers, Training - Universal ML computational primitives everyone needs 🧠 Intelligence Tier (08-13): Modern AI algorithms implementation - DataLoader, Spatial, Tokenization, Embeddings, Attention, Transformers - Core algorithms that define modern ML systems (not "applications") ⚡ Optimization Tier (14-19): Production systems engineering - KV-Caching, Profiling, Acceleration, Quantization, Compression, Benchmarking - Making intelligent algorithms fast, efficient, and scalable 🏅 Capstone Project (20): AI Olympics integration This mirrors real ML systems engineering roles and builds proper conceptual understanding for production ML systems work. Students need to understand the intelligence algorithms before they can optimize them effectively. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
92 lines
2.2 KiB
YAML
92 lines
2.2 KiB
YAML
# TinyTorch: Build ML Systems from Scratch
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# Table of Contents Structure
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format: jb-book
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root: intro
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title: "TinyTorch Course"
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parts:
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- caption: 🚀 Getting Started
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chapters:
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- file: quickstart-guide
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title: "Quick Start Guide"
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- file: usage-paths/classroom-use
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title: "For Instructors"
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- caption: 🛠️ Using TinyTorch
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chapters:
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- file: tito-essentials
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title: "Essential Commands"
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- file: learning-progress
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title: "Track Your Progress"
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- caption: 🧭 Course Orientation
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chapters:
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- file: chapters/00-introduction
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title: "Introduction"
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- caption: 🏗️ Foundation Tier (01-07)
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chapters:
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- file: chapters/01-tensor
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title: "01. Tensor"
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- file: chapters/02-activations
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title: "02. Activations"
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- file: chapters/03-layers
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title: "03. Layers"
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- file: chapters/04-losses
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title: "04. Losses"
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- file: chapters/05-autograd
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title: "05. Autograd"
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- file: chapters/06-optimizers
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title: "06. Optimizers"
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- file: chapters/07-training
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title: "07. Training"
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- caption: 🧠 Intelligence Tier (08-13)
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chapters:
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- file: chapters/08-dataloader
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title: "08. DataLoader"
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- file: chapters/09-spatial
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title: "09. Spatial"
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- file: chapters/10-tokenization
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title: "10. Tokenization"
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- file: chapters/11-embeddings
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title: "11. Embeddings"
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- file: chapters/12-attention
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title: "12. Attention"
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- file: chapters/13-transformers
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title: "13. Transformers"
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- caption: ⚡ Optimization Tier (14-19)
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chapters:
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- file: chapters/14-kvcaching
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title: "14. KV Caching"
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- file: chapters/15-profiling
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title: "15. Profiling"
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- file: chapters/16-acceleration
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title: "16. Acceleration"
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- file: chapters/17-quantization
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title: "17. Quantization"
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- file: chapters/18-compression
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title: "18. Compression"
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- file: chapters/19-benchmarking
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title: "19. Benchmarking"
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- caption: 🏅 Capstone Project
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chapters:
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- file: chapters/20-capstone
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title: "20. AI Olympics"
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- caption: 🌍 Community
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chapters:
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- file: community
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title: "Ecosystem"
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- caption: 🛠️ Resources & Tools
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chapters:
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- file: checkpoint-system
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title: "Progress Tracking"
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- file: testing-framework
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title: "Testing Guide"
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- file: resources
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title: "Additional Resources" |