Teaching Machine Learning for the Physical Sciences: A summary of lessons learned and challenges

Viviana Acquaviva

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arXiv · 2108.08313

Teaching Machine Learning for the Physical Sciences: A summary of lessons learned and challenges

Viviana Acquaviva

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Abstract

This paper summarizes some challenges encountered and best practices established in several years of teaching Machine Learning for the Physical Sciences at the undergraduate and graduate level. I discuss motivations for teaching ML to physicists, desirable properties of pedagogical materials, such as accessibility, relevance, and likeness to real-world research problems, and give examples of components of teaching units.

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Viviana Acquaviva. 2021-08-18. Teaching Machine Learning for the Physical Sciences: A summary of lessons learned and challenges. https://arxiv.org/abs/2108.08313

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