Various Course Proposals for: Mathematics with a View Towards (the Theoretical Underpinnings of) Machine Learning

264 Pages Posted: 16 Sep 2021 Last revised: 5 May 2022

See all articles by Marc S. Paolella

Marc S. Paolella

University of Zurich - Department of Banking and Finance; Swiss Finance Institute

Date Written: September 14, 2021

Abstract

In light of the growing use, acceptance of, and demand for, machine learning in many fields, notably data science, but also other fields such as finance -- and this in both industry and academics, some university departments might wish, or find themselves forced to, accord to the winds of change and address this pressing issue. The goal of this document is to assist in designing relevant courses using material at the appropriate mathematical level. It protocols, sorts, evaluates, and contrasts, numerous viable books for a variety of possible courses. The subjects span several levels of, and different avenues in, linear algebra and real analysis, with briefer discussions of material in probability theory and mathematical finance.

Suggested Citation

Paolella, Marc S., Various Course Proposals for: Mathematics with a View Towards (the Theoretical Underpinnings of) Machine Learning (September 14, 2021). Swiss Finance Institute Research Paper No. 21-65, Available at SSRN: https://ssrn.com/abstract=3923528 or http://dx.doi.org/10.2139/ssrn.3923528

Marc S. Paolella (Contact Author)

University of Zurich - Department of Banking and Finance

Plattenstr. 14
Zürich, 8032
Switzerland

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

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