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

Marc S. Paolella
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Marc S. Paolella: University of Zurich - Department of Banking and Finance; Swiss Finance Institute

No 21-65, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

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.

Pages: 223 pages
Date: 2021-09
New Economics Papers: this item is included in nep-big and nep-isf
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2165

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