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![NumPy](https://img.shields.io/badge/numpy-%E2%9C%94-lightgrey)
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[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
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![MNIST](https://img.shields.io/badge/dataset-MNIST-orange)
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<h1 align="center">🧠 CNN from Scratch on MNIST</h1>
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<h1 align="center">CNN from Scratch on MNIST</h1>
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This project implements a simple Convolutional Neural Network (CNN) using **NumPy only**, without any deep learning frameworks like TensorFlow or PyTorch.
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It trains on the **MNIST handwritten digit dataset** (28×28 grayscale images) and includes forward and backward propagation, convolution, pooling, dense layers, softmax + cross-entropy loss, and SGD optimizer with momentum + decay.

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