AI Chess Player

An intelligent chess engine that learns to play through self-play rather than hard-coded rules. Built on a deep reinforcement learning approach, the system pairs a neural network for board evaluation and move prediction with a search strategy that improves its play over successive training generations — learning openings, tactics, and endgame patterns purely from experience.
The model was trained in Python using TensorFlow, with the network learning to estimate position strength and select strong candidate moves without relying on a traditional opening book or brute-force lookup.

Shorter card version (for a portfolio grid tile):
A self-learning chess engine trained via deep reinforcement learning. A neural network evaluates positions and predicts moves, improving through self-play instead of hand-written rules. Built in Python with TensorFlow.