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MAS 4115

Linear Algebra for Data Science

University of Florida 3 credits Mathematics

Course Description

A second course in linear algebra, focusing on topics that are the most essential for data science. Introduces theory and numerical methods required for large data-sets and machine learning. Topics include LU, QR, and singular-value decompositions; conditioning and stability; the DFT and filters; deep learning; fully connected and convolutional nets. Prerequisite: (MAS 3114 or MAS 4105) and MAC 2313.

Code
MAS 4115
Credits
3
Subject
Mathematics

Programs That Include This Course

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