CNN Model for MNIST Digit Classification

This repository contains a Convolutional Neural Network (CNN) model trained on the MNIST dataset for digit classification. The model has achieved an accuracy of 99% on the test dataset and is available for use as a TensorFlow model.

Model Details

• Architecture: Convolutional Neural Network (CNN)
• Input Size: 28x28 pixels with 1 channel (grayscale)
• Data Preprocessing: The model has been trained on normalized data.
• Accuracy: 99%

Usage

You can use this model for digit classification tasks. Below are some code snippets to help you get started:

# Load the model and perform inference
import tensorflow as tf
model = tf.keras.models.load_model('model.h5')

# Perform inference
predictions = model.predict(image)

# Get the predicted digit
predicted_digit = np.argmax(predictions)