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Unsupervised Learning

This Repository is a primitive unspervised learning model that employs an autoencoder with a clustering layer to "learn" and sort data. This model works with the MNIST dataset and achieves an unsupervised sorting accuracy of 71%

This is of course a very simplified model and can be updated to include the clustering results in the loss function. Which will be implemented in the future with further understanding of the math and intuition behind its implementation.

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