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This project implements a handwritten digit recognition system using deep learning techniques. The system can accurately classify handwritten digits (0–9) from images using a Convolutional Neural Network (CNN) trained on the MNIST dataset. It demonstrates the power of neural networks in image recognition and AI-driven pattern detection.

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Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
1. K Nearest Neighbors		1. K Nearest Neighbors
2. SVM		2. SVM
3. Random Forest Classifier		3. Random Forest Classifier
CNN_Keras		CNN_Keras
MNIST_Dataset_Loader		MNIST_Dataset_Loader
Outputs		Outputs
Results		Results
dataset		dataset
README.md		README.md

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HandwrittenDigitRecognitionusingDeep-Learning

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This project implements a handwritten digit recognition system using deep learning techniques. The system can accurately classify handwritten digits (0–9) from images using a Convolutional Neural Network (CNN) trained on the MNIST dataset. It demonstrates the power of neural networks in image recognition and AI-driven pattern detection.

handwrittendigitrecognitionusingdeep-learning

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