This introduces a complete visual overview system for TinyTorch that provides:
- Interactive dependency graph visualization of all 17 modules
- Comprehensive system architecture diagrams with layered components
- Automated learning roadmap generation with optimal module sequence
- Component analysis tools for understanding module complexity
- ML systems thinking questions connecting education to industry
- Export functions for programmatic access to framework metadata
The module serves as the entry point for new learners, providing complete
context for the TinyTorch learning journey and helping students understand
how all components work together to create a production ML framework.
Key features:
- TinyTorchAnalyzer class for automated module discovery and analysis
- NetworkX-based dependency graph construction and visualization
- Matplotlib-powered interactive diagrams and charts
- Comprehensive testing suite validating all functionality
- Integration with existing TinyTorch module workflow
