A machine learning playground for experimenting with various ML models and techniques.
Open any HTML file in visualizations/ in your browser.
Interactive Q-Learning reinforcement learning demonstration featuring a Pac-Man agent learning to navigate a maze and collect dots while avoiding ghosts. Built with HTML5 Canvas and JavaScript, this demo showcases RL concepts including Q-value visualization, hyperparameter tuning, and training progress monitoring.
Image generation and reconstruction models including autoencoders, VAEs, and planned implementations of GANs, Stable Diffusion, and Diffusion Transformers (DiT).
Sentence embedding learning using SimCSE approach.
Docker-based environment for LLM post-training experiments.
