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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information.


Fall 2021 Mathematics GR5430 section 001
Machine Learning for Finance
Machine Learning for Fina

Call Number 10786
Day & Time
Location
R 8:10pm-10:00pm
312 Mathematics Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Renzo Silva
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 35 students (50 max) as of 9:06PM Friday, November 26, 2021
Subject Mathematics
Number GR5430
Section 001
Division Interfaculty
Campus Morningside
Note MAFN Students ONLY. Open to STATS 9/7. Open to Univ. 9/13
Section key 20213MATH5430G001

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SIS update 11/26/21 21:06    web update 11/26/21 21:23