- Combine venv setup and tito execution in same step
- Add pytest installation for tito environment validation
- Add explanatory comments about GitHub Actions shell behavior
- Remove environment skipping hack in favor of proper setup
- Workflow now uses tito CLI consistently for book generation
✅ Remove unnecessary nesting: book/tinytorch-course/ → book/
✅ Update all path references in scripts and workflows
✅ Cleaner development experience with shorter paths
✅ Book builds successfully with simplified structure
Changes:
- Move all book files up one directory level
- Update convert_modules.py paths
- Update GitHub Actions workflow paths
- Update book configuration paths
- Test confirms everything works correctly
✅ Add learning goals extraction with beautiful admonition blocks
✅ Create hybrid book approach (overview pages + interactive buttons)
✅ Generate both notebooks (Binder/Colab) and book pages
✅ Update GitHub Actions for main branch deployment
✅ All 14 modules now have consistent formatting
Features:
- Extract content from source files (no duplication)
- Interactive launch buttons (GitHub/Binder/Colab)
- Learning objectives as 🎯 tip admonitions
- Notebooks generated in-place for direct access
- Clean separation: dev → main → website deployment
- Changed trigger from main to dev branch (repository default)
- Updated deploy condition to check for dev branch
- Ensures workflow runs on correct branch for this repository
- Add module conversion step before book building
- Install jupytext dependency for conversion script
- Maintains existing GitHub Pages deployment pipeline
- Automatically converts modules/source/ to notebooks on deploy
- Created interactive Jupyter Book structure in book/tinytorch-course/
- Configured for GitHub Pages, Binder, and Colab integration
- Set up automated deployment with GitHub Actions
- Designed comprehensive course structure with 4 main parts:
* Foundation (Setup, Tensors, Activations)
* Building Blocks (Layers, Networks, CNNs)
* Training Systems (DataLoader, Autograd, Optimizers, Training)
* Production & Performance (Compression, Kernels, Benchmarking, MLOps)
- Added engaging introduction with interactive features
- Ready for module conversion from *_dev.py to executable notebooks
Next: Convert modules/source/*_dev.py files to interactive chapters
