Teaching Computational Machine Learning (without Statistics)

Authors

Katherine M. Kinnaird, Smith CollegeFollow

Document Type

Article

Publication Date

9-14-2020

Publication Title

Teaching Machine Learning Workshop at ECML-PKDD 2020

Abstract

This paper presents an undergraduate machine learning course that emphasizes algorithmic understanding and programming skills while assuming no statistical training. Emphasizing the development of good habits of mind, this course trains students to be independent machine learning practitioners through an iterative, cyclical framework for teaching concepts while adding increasing depth and nuance. Beginning with unsupervised learning, this course is sequenced as a series of machine learning ideas and concepts with specific algorithms acting as concrete examples. This paper also details course organization including evaluation practices and logistics.

Comments

Archived as published.

Teaching Machine Learning Workshop at ECML-PKDD 2020, Virtual (formerly Ghent, Belgium) Sept. 14, 2020.

Originally published at: http://proceedings.mlr.press/v141/kinnaird21a

Recommended Citation

Kinnaird, Katherine M., "Teaching Computational Machine Learning (without Statistics)" (2020). Statistical and Data Sciences: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/sds_facpubs/42

Rights

Copyright 2020 by the author.