Handwritten Digit Recognition Project

Description:

This project aims to develop a machine learning model to recognize handwritten digits using the MNIST dataset. The project leverages various Python libraries for data processing, model training, and evaluation.

Features:

Data Loading and Preprocessing: Load and preprocess the MNIST dataset.

Model Training: Train a RandomForestClassifier to recognize digits.

Model Evaluation: Evaluate the model's performance using various metrics.

Visualization: Visualize the data and the model's performance using Matplotlib and Seaborn.