TinyTorch/docs

📚 TinyTorch Documentation

Welcome to the TinyTorch documentation! This directory contains guides organized by audience and purpose.

🎯 Find Your Documentation

🎓 Students (Taking the ML Systems Course)

Start here if you're learning ML systems:

• Project Guide - Track your progress through all 12 modules
• Quickstart - Get up and running quickly
• Main README - Project overview and introduction

👨‍🏫 Instructors (Teaching or Designing the Course)

Understanding the educational philosophy:

• Pedagogical Principles - The "Build → Use → Understand" framework
• Vision - High-level course philosophy and learning approach
• Testing Architecture - Dual testing system for education

🔧 Human Developers (Building New Modules)

Creating or contributing to TinyTorch modules:

• Development Guide - Start here for complete development methodology
• Module Development Guide - Educational design and best practices
• Module Creation Checklist - Step-by-step process
• Quick Reference - Commands and common patterns

🤖 AI Assistants (Development Support)

Coding patterns and quality enforcement:

• .cursor/rules/ - Specific implementation patterns, code examples, and anti-patterns
• Automatic guidance during development through cursor rules

📊 Documentation Architecture

Clear Audience Separation

docs/
├── students/           # 🎓 Course participants
│   └── project-guide.md    # Module progression and workflow
├── pedagogy/          # 👨‍🏫 Instructors and course designers  
│   ├── pedagogical-principles.md  # Educational theory
│   ├── vision.md              # Course philosophy
│   └── testing-architecture.md   # Assessment strategy
├── development/       # 🔧 Human module developers
│   ├── README.md              # Development methodology
│   ├── module-development-guide.md  # Complete guide
│   ├── module-creation-checklist.md # Step-by-step process
│   └── quick-module-reference.md   # Commands and patterns
└── README.md          # 📍 This file - navigation hub

.cursor/rules/         # 🤖 AI assistants (not in docs/)
├── module-development-best-practices.mdc  # Coding patterns
├── testing-patterns.mdc                   # Test requirements
└── nbdev-educational-pattern.mdc          # NBDev structure

No Duplication by Design

• Students: Course navigation and module progression
• Instructors: Educational philosophy and theory
• Human Developers: Methodology, workflow, and educational design
• AI Assistants: Specific coding patterns and implementation examples

🚀 Quick Navigation

I am a...	I want to...	Go to...
Student	Start the course	Project Guide
Student	Get unstuck on setup	Quickstart
Instructor	Understand the pedagogy	Pedagogical Principles
Instructor	Design a new course	Vision
Developer	Build a new module	Development Guide
Developer	Need quick help	Quick Reference
Contributor	Understand the philosophy	Pedagogical Principles

🔑 Core Principles (Across All Documentation)

Educational Excellence

• "Build → Use → Understand → Repeat" - Every module follows this cycle
• Real-world relevance - Connect to production ML engineering
• Immediate feedback - Students see their code working
• Progressive complexity - Build understanding step by step

Real Data, Real Systems

• Use production datasets (CIFAR-10, ImageNet), not synthetic data
• Include progress feedback for downloads and long operations
• Test with realistic scales and performance constraints
• Think about caching, user experience, and systems concerns

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All documentation follows the TinyTorch principle: Build → Use → Understand → Repeat