# Mathematical Aspects of Machine Learning

Jeremy Teitelbaum

University of Connecticut

Department of Mathematics

Math 5800, Spring Term 2020

**Description:** This is a project-based course in which students will explore both practical and mathematical problems arising in machine learning and data science. Possible topics include random walks for graph embeddings, optimization techniques, Monte Carlo methods, autoencoders, and linear and non-linear dimension reduction.

### Course background

### References

### Assignments