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Repository of UvA's lab exercises for the course "Machine Learning 2" 2019.

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Machine Learning 2

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Repository of UvA's lab exercises for the course "Machine Learning 2" 2019.

In this assignment, we implement the Independent Component Analysis algorithm, as described in chapter 34 of David MacKay's book "Information Theory, Inference, and Learning Algorithms".

Results of signal reconstruction using different priors and W matrix initialization.

In this assignment, we implement the sum-product and max-sum algorithms for factor graphs over discrete variables. We implemented these algorithms to a medical graph, in order to infer the possible decease.

Medical Directed Graph.

In this assignment, we implement the Expectation Maximization (EM) algorithm and Variational Autoencoder (VAE) on the MNIST dataset of written digits.

VAE's leanred manifold of the MNIST dataset of written digits.

Acknowledgement - References

The majority of the projects come from the lab assignments of the Machine Learning 2 course of the MSc in Artificial Intelligence at the University of Amsterdam.