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A Gaussian Bayes Classifier in Python for MNIST

In this post I present my learning of the concepts of a simple Gaussian Bayes classifier using the MNIST data. The objective is to show the capabilities of a "generative" model as a prelude to a Generative Adversarial Network and its applications. The solution is built around the calculation of the mean and co-variance of data clusters for a particular class. The classes are formed by singular digits from the MNIST dataset. We will utilize the package Scipy and the function s