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✨ Complete standardization of all TinyTorch module READMEs: 📊 **Module Info**: Consistent difficulty, time, prerequisites, next steps 🎯 **Learning Objectives**: Clear, measurable, action-oriented outcomes 🧠 **Pedagogical Framework**: Build → Use → [Context-specific verb] 📚 **What You'll Build**: Concrete code examples and implementations 🚀 **Getting Started**: Prerequisites check + development workflow 🧪 **Testing**: Comprehensive test coverage + inline feedback 🎯 **Key Concepts**: Real-world applications + technical foundations 🎉 **Ready to Build**: Motivational + grid cards for all modules ✅ All 14 modules now follow identical structure: - 01_setup: Foundation workflow mastery - 02_tensor: Core data structures - 03_activations: Neural network fundamentals - 04_layers: Building blocks - 05_networks: Architecture design - 06_cnn: Computer vision foundations - 07_dataloader: Data pipeline engineering - 08_autograd: Automatic differentiation - 09_optimizers: Learning algorithms - 10_training: End-to-end orchestration - 11_compression: Model optimization - 12_kernels: Performance optimization - 13_benchmarking: Systematic evaluation - 14_mlops: Production deployment (capstone) 🎓 **Student Experience**: Predictable navigation, clear expectations, motivational flow 👨🏫 **Instructor Experience**: Professional consistency, easy maintenance, coherent course This establishes the single source of truth that will automatically convert to clean website chapters via book/convert_readmes.py