Mathematical foundations of data anlaysis

  • Lecturer: Samantha Fairchild
  • Date: Tuesdays 11:15-12:45 and Wednesdays 15:15-16:45
  • Room: SG 2-14
  • Audience: Masters level course, but still of interest to PhD students and postdocs wanting to become familiar with data science terms
  • Keywords: Linear algebra, probability theory, network analysis, machine learning, topological data analysis, tensors

Abstract

This course is designed so someone can understand the definitions of standard data science terms, and the associated mathematical terms. We also give proofs of how commonly used techniques in data science work along with implementing algorithms and examples with a computer program. We start by covering Linear algebra and Probability necessary for the course, and then proceed in 4 different topics: network analysis, machine learning, topological data analysis, and then low rank matrices and tensor.

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Regular lectures: Winter semester 2022/2023

09.12.2022, 02:30