From cf8e4b6e7dc69f220f0aa87cad063519a4eaa9fc Mon Sep 17 00:00:00 2001 From: Vijay Janapa Reddi Date: Fri, 18 Jul 2025 08:54:30 -0400 Subject: [PATCH] =?UTF-8?q?=F0=9F=93=9A=20Update=20intro.md=20to=20reflect?= =?UTF-8?q?=20current=2016-module=20structure?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit πŸ”„ Module Structure Updates: - Updated from 15 to 16 modules in course journey - Fixed module names: Networks β†’ Dense, CNNs β†’ Spatial - Added new 07_attention module to Building Blocks section - Updated all subsequent module numbering (8-16) 🎨 Section Improvements: - Renamed 'Production & Performance' β†’ 'Inference & Serving' (more accurate) - Added 16_capstone to final section with 'advanced framework engineering' - Updated descriptions to include attention mechanisms and capstone project πŸ“Š Accurate Course Progression: - Foundation: 01-03 (Setup, Tensors, Activations) - Building Blocks: 04-07 (Layers, Dense, Spatial, Attention) - Training Systems: 08-11 (DataLoader, Autograd, Optimizers, Training) - Inference & Serving: 12-16 (Compression, Kernels, Benchmarking, MLOps, Capstone) Result: Book intro now accurately reflects the current repository structure and improved section naming for better clarity. --- book/intro.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/book/intro.md b/book/intro.md index 3542d82a..86eda7ca 100644 --- a/book/intro.md +++ b/book/intro.md @@ -14,7 +14,7 @@ html_meta: # TinyπŸ”₯Torch -## Build your own Machine Learning framework from scratch. +## Build your own ML framework. Start small. Go deep. **Most ML education teaches you to _use_ frameworks. TinyTorch teaches you to _build_ them.** @@ -99,7 +99,7 @@ This pattern repeats for every component: tensors, layers, optimizers, even MLOp --- -## πŸ“š **Course Journey: 15 Modules** +## πŸ“š **Course Journey: 16 Modules** ```{admonition} πŸ—οΈ Foundation :class: note @@ -110,23 +110,23 @@ Understanding workflow, multi-dimensional arrays, and the mathematical functions ```{admonition} 🧱 Building Blocks :class: note -**4. Layers** β€’ **5. Networks** β€’ **6. CNNs** +**4. Layers** β€’ **5. Dense** β€’ **6. Spatial** β€’ **7. Attention** -Dense layers, sequential architecture, and convolutional operations for computer vision. +Dense layers, sequential networks, convolutional operations, and self-attention mechanisms. ``` ```{admonition} 🎯 Training Systems :class: note -**7. DataLoader** β€’ **8. Autograd** β€’ **9. Optimizers** β€’ **10. Training** +**8. DataLoader** β€’ **9. Autograd** β€’ **10. Optimizers** β€’ **11. Training** CIFAR-10 loading, automatic differentiation, SGD/Adam optimizers, and complete training orchestration. ``` -```{admonition} ⚑ Production & Performance +```{admonition} πŸš€ Inference & Serving :class: note -**11. Compression** β€’ **12. Kernels** β€’ **13. Benchmarking** β€’ **14. MLOps** +**12. Compression** β€’ **13. Kernels** β€’ **14. Benchmarking** β€’ **15. MLOps** β€’ **16. Capstone** -Model optimization, high-performance operations, systematic evaluation, and production monitoring. +Model optimization, high-performance operations, systematic evaluation, production monitoring, and advanced framework engineering. ``` ```{admonition} πŸŽ“ Capstone Project