Reinforcement Learning Chess Agent

Implemented Q-Learning and Deep Q-Networks (DQN) to train a chess AI agent. The agent learns to maximize rewards through piece capture, board control, and achieving winning states.

Computer Vision Bicep Comparison

This script applies computer vision techniques to analyze and compare biceps in images by detecting edges, extracting contours, and measuring size and definition. It uses the contour area formula to estimate bicep size and the Laplacian variance method to assess muscle definition by measuring image sharpness. These calculations provide a quantitative way to compare muscle growth and conditioning using image processing.