The project aims at classifying handwritten digits from the MNIST dataset by training the data on a simple CNN model. The dataset is from kaggle and is part of the competition-Digit recognizer on Kaggle. The model classifies with an accuracy of nearly 99% (0.998).
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aminarifa/MNIST-Handwritten-Digits-Recognizer
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Digits classification using CNNs on MNIST Dataset
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