This report talks about the development of a solution for the classification problem of handwritten digits of the MNIST dataset, divided into two parts, the first using Multilayer Perceptron Neural Networks (MLP) and the second Convolutional Neural Networks (CNN). The MNIST dataset consists of 70,000 28x28 images from the digits 0 to 9, with 60,000 training samples and 10,000 test samples.
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