Use a convolutional neural network to classify handwritten digits from the MNIST dataset. A variety of architectures and hyperparameters were tested, and the best model (submitted to Kaggle) used an ensemble of ResNet-type models. The accuracy on the test set for this model was 99.585%.
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Recognize handwritten digits from the MNIST dataset
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