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).