This repository contains a machine learning model designed to classify handwritten images (digits) It leverages Convolutional Neural Networks (CNNs) for accurate and efficient classification.
Features: Dataset: Trained on the [MNIST], ensuring robust performance. Preprocessing: Includes resizing, normalization, and data augmentation for better generalization. Architecture: A CNN-based architecture optimized for feature extraction and classification. Performance: Achieves [97]% accuracy on the test dataset. Deployment: Model is ready for integration into real-world applications like OCR systems, form processing, and postal code recognition.