Math 3094

Honors Undergraduate Course on Machine Learning

View the Project on GitHub jeremy9959/Math-3094-Spring-2021

Honors Seminar in Machine Learning

Math 3094, Spring Semester 2021
University of Connecticut

Instructors

Introduction

The interdisciplinary field known as Machine Learning or Data Science draws together techniques from computer science, mathematics, and statistics to extract meaning from data. In this course, we will discuss some of the essential mathematical ideas in this field.

While our focus will be on the role of Calculus, Probability, and Linear Algebra, we will introduce computational techniques using Python and the Jupyter notebook environment, and some ideas from statistics, in order to closely link theory and practice.

Schedule

The course will meet synchronously online on Tuesdays and Thursdays from 11:00 to 12:15 EST using BlackBoard Collaborate through the HuskyCT UConn LMS.

Topics

An outline of the course topics is available here.

A guide to the first assigned project is here

Resources

We will use the Campus Wire platform for online help and discussions. Students enrolled in the course should receive an electronic invite to the forum. Contact one of the professors if you need access.

We will rely on the Python programming language, the Anaconda open source data science platform, and the Jupyter notebook environment for our computer work. All of this software can be obtained for Linux, Mac, or Windows from the Anaconda website: www.anaconda.com.

A very brief guide to installing the software is available here.

There is no official textbook for the course. We will be providing notes as we progress. The following texts may be useful as references.