/Machine-Learning-2

Projects from the Machine learning 2 Course on ICA, Inference in Graphical models, EM algorithm and VAE (October, 2020).

Primary LanguageJupyter Notebook

Machine Learning 2 Labs

This repository contains Labs from the Machine Learning 2 Course from the Master Artificial Intelligence at the UvA in September-October 2020.

Lab 1: Independent Component Analysis (ICA)

This lab implements the Independent Component Analysis algorithm as described in chapter 34 of David MacKay's book "Information Theory, Inference, and Learning Algorithms".

Lab 2: Inference in Graphical Models

The goal of this lab is to implement sum-product and max-sum algorithms for factor graphs over discrete variables.

Lab 3: Variational Autoencoder (VAE)

This lab covers the implementation of the Expectation Maximization (EM) algorithm and the Variational Auto-Encoder (VAE), first introduced by Diederik Kingma and Max Welling in 2013.