Implemented a variety of reinforcement learning algorithms from scratch using Numpy and PyTorch with extensive theoretical explanation in a blog-like style. For example: Variants of MC & TD, Deep Q-Network & variants, Policy Gradient algorithms (like REINFORCE, A2C, etc.)
Implemented a variety of deep generative learning models from scratch using PyTorch with extensive theoretical explanation in a blog-like style. For example: VAE, GAN & variants (like WGAN, Conditional GAN, etc.), DDPM, etc.
Implemented miscellaneous deep learning models (eg: Transformer, U-Net, etc.) from scratch using PyTorch.