Research Highlights: Pen and Paper Exercises in Machine Learning

Print Friendly, PDF & Email

Title: Pen and Paper Exercises in Machine Learning

This paper consists of a collection of (mostly) pen-and-paper exercises in machine learning. The exercises are on the following topics: linear algebra, optimization, directed graphical models, undirected graphical models, expressive power of graphical models, factor graphs and message passing, inference for hidden Markov models, model-based learning (including ICA and unnormalized models), sampling and Monte-Carlo integration, and variational inference. Highly recommended for data scientists wishing to evolve their understanding of the mathematical foundations of the field.

Sign up for the free insideAI News newsletter.

Join us on Twitter: https://twitter.com/InsideBigData1

Join us on LinkedIn: https://www.linkedin.com/company/insidebigdata/

Join us on Facebook: https://www.facebook.com/insideAI NewsNOW

Speak Your Mind

*