michaelgutmann/ml-pen-and-paper-exercises
A LaTeX collection of pen-and-paper exercises with detailed solutions covering machine learning mathematics and theory.
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This repository contains educational exercises in machine learning with full solutions, covering topics including linear algebra, optimization, directed and undirected graphical models, factor graphs, message passing, hidden Markov models, independent component analysis, Monte Carlo sampling, and variational inference. The material is compiled from LaTeX source into a PDF published on arXiv and is designed for learning and teaching ML concepts through worked examples.
Frequently asked
- What is michaelgutmann/ml-pen-and-paper-exercises?
- A LaTeX collection of pen-and-paper exercises with detailed solutions covering machine learning mathematics and theory.
- Is ml-pen-and-paper-exercises open source?
- Yes — michaelgutmann/ml-pen-and-paper-exercises is an open-source project tracked on heatdrop.
- What language is ml-pen-and-paper-exercises written in?
- michaelgutmann/ml-pen-and-paper-exercises is primarily written in TeX.
- How popular is ml-pen-and-paper-exercises?
- michaelgutmann/ml-pen-and-paper-exercises has 2.7k stars on GitHub.
- Where can I find ml-pen-and-paper-exercises?
- michaelgutmann/ml-pen-and-paper-exercises is on GitHub at https://github.com/michaelgutmann/ml-pen-and-paper-exercises.