MNIST Digit Image Classification Deep Learning Project Overview: This project focuses on building a deep learning model to classify handwritten digits from the MNIST dataset.

Objective: The goal is to train a neural network to accurately recognize digits

Key Features: Data Preprocessing Model Development Training and Evaluation

Technologies Used: Python TensorFlow Keras (for model building) Matplotlib (for visualization)

Dataset: Utilizing the MNIST dataset, which consists of 28x28 pixel grayscale images of handwritten digits (0-9).