Abstract
One of the principal goals of machine learning is to learn in an automated way functions that represent the relationship between data points.
Chapter PDF
Author information
Authors and Affiliations
Rights and permissions
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Copyright information
© 2024 The Author(s)
About this chapter
Cite this chapter
Breiding, P., Kohn, K., Sturmfels, B. (2024). Machine Learning. In: Metric Algebraic Geometry. Oberwolfach Seminars, vol 53. Birkhäuser, Cham. https://doi.org/10.1007/978-3-031-51462-3_10
Download citation
DOI: https://doi.org/10.1007/978-3-031-51462-3_10
Published:
Publisher Name: Birkhäuser, Cham
Print ISBN: 978-3-031-51461-6
Online ISBN: 978-3-031-51462-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)