Handwritten Digit Classification System

Developed a system to classify handwritten digits (0-9) using Decision Trees, Neural Networks, and Genetic Algorithms. Applied

Principal Component Analysis (PCA) for dimensionality reduction, improving model efficiency and accuracy. Evaluated model

performance using comprehensive datasets and deployed the best-performing model for practical applications.