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SDS 326E

Elements of Statistical Machine Learning

The University of Texas at Austin 3 credits Statistics and Data Sciences

Course Description

Introduction to the concepts and tools of data science, statistics, and machine learning used to draw inferences about large-scale and real-world data. Explore data visualization, linear and nonlinear models, regularization, classification, resampling, tree-based methods, support vector machines, and unsupervised learning. Statistics and Data Sciences 323 and 326E may not both be counted. Three lecture hours a week for one semester. Pre/Corequisites: Statistics and Data Sciences 320E, 322E, and Statistics and Data Sciences 321 or Mathematics 362K.

Code
SDS 326E
Credits
3
Subject
Statistics and Data Sciences

Programs That Include This Course

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