digit prediction using cnn add den prediction models

[deepanshubaghel]

Description

This project implements a Convolutional Neural Network (CNN) to classify digits using the MNIST dataset. It includes:

• Data Preprocessing: Images are normalized and augmented for better generalization.
• CNN Architecture: The model consists of multiple Conv2D, MaxPooling, and Dropout layers, culminating in a softmax layer for digit classification.
• Training: The model is trained using the Adam optimizer and sparse categorical crossentropy loss, with real-time data augmentation to enhance model robustness.
• Evaluation: Validation accuracy and loss metrics are tracked over 50 epochs, with visualizations to analyze performance.
• Prediction: Final predictions on the test dataset are provided with visual output for a sample of the test images.

Fixes #1321

Checklist:

• My code follows the style guidelines of this project
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings

[github-actions]

Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. In the meantime, please ensure that your changes align with our CONTRIBUTING.md. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊