@KirkDBorne: "Pen and Paper Exercises in Machine Learning" Download 211-page PDF: http://arxiv.org/abs/2206.13446 Author’s GitHub: h…

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This paper provides a 211-page collection of pen-and-paper exercises covering key topics in machine learning, including linear algebra, optimisation, graphical models, and variational inference, intended as an educational resource.

"Pen and Paper Exercises in Machine Learning" Download 211-page PDF: http://arxiv.org/abs/2206.13446 Author’s GitHub: https://github.com/michaelgutmann/ml-pen-and-paper-exercises… ————— #DataScientist #AI #ML #DataScience
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“Pen and Paper Exercises in Machine Learning” Download 211-page PDF: http://arxiv.org/abs/2206.13446 Author’s GitHub: https://github.com/michaelgutmann/ml-pen-and-paper-exercises… ————— #DataScientist #AI #ML #DataScience

Pen and Paper Exercises in Machine Learning

Source: https://arxiv.org/abs/2206.13446 View PDF

Abstract: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 hidden Markov models, model-based learning (including ICA and unnormalised models), sampling and Monte-Carlo integration, and variational inference.

Submission history

From: Michael Gutmann [view email] **[v1]**Mon, 27 Jun 2022 16:53:18 UTC (1,679 KB)

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