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Enhanced all remaining modules with comprehensive educational content: ## Modules Updated - ✅ 03_layers: Added NBGrader metadata, solution blocks for matmul_naive and Dense class - ✅ 04_networks: Added NBGrader metadata, solution blocks for Sequential class and forward pass - ✅ 05_cnn: Added NBGrader metadata, solution blocks for conv2d_naive function and Conv2D class - ✅ 06_dataloader: Added NBGrader metadata, solution blocks for Dataset base class ## Key Features Added - **NBGrader Metadata**: All cells properly tagged with grade, grade_id, locked, schema_version, solution, task flags - **Solution Blocks**: All TODO sections now have ### BEGIN SOLUTION / ### END SOLUTION markers - **Import Flexibility**: Robust import handling for development vs package usage - **Educational Content**: Package structure documentation and mathematical foundations - **Comprehensive Testing**: All modules run correctly as Python scripts ## Verification Results - ✅ All modules execute without errors - ✅ All solution blocks implemented correctly - ✅ Export workflow works: tito export --all successfully exports all modules - ✅ Package integration verified: all imports work correctly - ✅ Educational content preserved and enhanced ## Ready for Production - Complete NBGrader-compatible assignment system - Streamlined tito export command with automatic .py → .ipynb conversion - Comprehensive educational modules with real-world applications - Robust testing infrastructure for all components Total modules completed: 6/6 (setup, tensor, activations, layers, networks, cnn, dataloader)