Vijay Janapa Reddi 7da85b3572 🧱 Implement Layers module - Neural Network Building Blocks ...

✨ Features:
- Dense layer with Xavier initialization (y = Wx + b)
- Activation functions: ReLU, Sigmoid, Tanh
- Layer composition for building neural networks
- Comprehensive test suite (17 passed, 5 skipped stretch goals)
- Package-level integration tests (14 passed)
- Complete documentation and examples

🎯 Educational Design:
- Follows 'Build → Use → Understand' pedagogical framework
- Immediate visual feedback with working examples
- Progressive complexity from simple layers to full networks
- Students see neural networks as function composition

🧪 Testing Architecture:
- Module tests: 17/17 core tests pass, 5 stretch goals available
- Package tests: 14/14 integration tests pass
- Dual testing supports both learning and validation

📚 Complete Implementation:
- Dense layer with proper weight initialization
- Numerically stable activation functions
- Batch processing support
- Real-world examples (image classification network)
- CLI integration: 'tito test --module layers'

This establishes the fundamental building blocks students need
to understand neural networks before diving into training.

2025-07-10 20:30:31 -04:00

..

__init__.py

Been refactoring the structure, got setup working

2025-07-10 11:13:45 -04:00

test_layers.py

🧱 Implement Layers module - Neural Network Building Blocks

2025-07-10 20:30:31 -04:00

test_setup.py

feat: Complete Setup module and enhance CLI functionality

2025-07-10 13:09:10 -04:00

test_tensor.py

Adds Tensor class with basic operations

2025-07-10 14:30:41 -04:00