Linear-Regression-from-Scratch

Linear Regression from Scratch: Math to Production A production-ready implementation of Linear Regression using only NumPy, demonstrating the mathematical foundations from gradient descent to scalable deployment.

Project Structure

linear-regression-scratch/
├── src/
│   ├── __init__.py
│   ├── model.py           # Core Linear Regression implementation
│   ├── train.py           # Training script
│   ├── utils.py           # Utility functions
│   └── config.py          # Configuration management
├── api/
│   ├── __init__.py
│   ├── main.py            # FastAPI application
│   ├── schemas.py         # Pydantic models
│   └── dependencies.py    # API dependencies
├── tests/
│   ├── __init__.py
│   ├── test_model.py      # Unit tests for model
│   ├── test_math.py       # Mathematical verification tests
│   └── test_api.py        # API integration tests
├── models/
│   └── (saved model files)
├── data/
│   └── (dataset files)
├── scripts/
│   └── verify_math.py     # Mathematical verification script
├── Dockerfile
├── .dockerignore
├── requirements.txt
├── requirements-dev.txt
├── Makefile
└── README.md