The MNIST database is a large database of handwritten digits that is commonly used for training various image processing systems. The database is also widely used for training and testing in the field of machine learning. The MNIST database contains 60,000 training images and 10,000 testing images.

In this notebook, we try to classify this database using a relatively simple convolutional neural network implemented in the PyTorch framework.

Result: After 3 epochs model training, we reached 97% accuracy.

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