A research-focused repository containing implementations and theoretical explorations of machine learning algorithms. The codebase emphasizes mathematical foundations, algorithmic efficiency, and reproducible research practices.
- Classical Machine Learning Algorithms
- Deep Learning Architectures
- Optimization Methods
- Statistical Learning Theory
- Reinforcement Learning
We welcome contributions that advance the theoretical understanding or practical implementation of machine learning algorithms. Please see our contribution guidelines for more information.