Image Classification Model using CNN

A deep learning model for recognizing handwritten digits (0–9) using a Convolutional Neural Network (CNN) built with Python and TensorFlow/Keras.

The model is trained on the MNIST dataset, which contains thousands of labeled images of handwritten digits. It learns to extract visual features and classify each image into the correct digit with high accuracy.

The project includes:

✔️ Data Preprocessing

✔️ Model Building & Training

✔️ Model Evaluation (Accuracy Metric)

✔️ Prediction on New Images

The model achieves high accuracy and can be used in applications such as digit recognition from images and forms.