Exercises in Machine Learning

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Machine Learning

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Exercises in Machine Learning

Pen and Paper Exercises in Machine Learning

This is a collection of (mostly) pen-and-paper exercises in machine learning.

The exercises are on the following topics: linear algebra, optimisation, directed graphical models, undirected graphical models, expressive power of graphical models, factor graphs and message passing, inference for hiddenmarkov models, model-based learning (including unnormalised models), sampling and monte-carlo integration, and variational inference.