A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

Tutorials and programming exercises for learning Q# and quantum computing

Datasets, tools, and benchmarks for representation learning of code.

The Numenta Anomaly Benchmark

PyTorch implementation of Soft Actor-Critic (SAC), Twin Delayed DDPG (TD3), Actor-Critic (AC/A2C), Proximal Policy Optimization (PPO), QT-Opt, PointNet..

Tabular data imputation and generation, with flexible modeling of quantitative features via hierarchical binning (TMLR, 2025)

Audio to midi conversion using deep learning and google nsynth dataset