Fall 2023 Mathematics GR5430 section 001

Machine Learning for Finance

Machine Learning for Fina

Call Number 10992
Day & Time
Location
T 12:10pm-2:00pm
717 Hamilton Hall
Points 3
Grading Mode Standard
Approvals Required None
Instructor William G Ritter
Type SEMINAR
Method of Instruction In-Person
Course Description

The application of Machine Learning (ML) algorithms in the Financial industry is now commonplace, but still nascent in its potential.  This course provides an overview of ML applications for finance use cases including trading, investment management, and consumer banking. 

Students will learn how to work with financial data and how to apply ML algorithms using the data.  In addition to providing an overview of the most commonly used ML models, we will detail the regression, KNN, NLP, and time series deep learning ML models using desktop and cloud technologies. 

The course is taught in Python using Numpy, Pandas, scikit-learn and other libraries.  Basic programming knowledge in any language is required.

Web Site Vergil
Department Mathematics
Enrollment 41 students (80 max) as of 9:07AM Tuesday, April 23, 2024
Subject Mathematics
Number GR5430
Section 001
Division Interfaculty
Campus Morningside
Note Priority to MAFN Students. Open to Stats 9/6 and Univ. 9/13
Section key 20233MATH5430G001