| Statistical Machine Learning - 60972 - CS 57800 - LE1 |
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Associated Term: Fall 2022
Levels: Undergraduate, Graduate, Professional West Lafayette Campus Lecture Schedule Type Learning Outcomes: In this graduate-level course on statistical machine learning, we will study three important classical aspects of statistical machine learning (time permitting): 1) Statistical inference: Topics include statistical distances, hypothesis testing, estimation theory, etc. 2) Supervised learning: Topics include classification, regression, neural networks, etc. 3) Unsupervised learning: Topics include dimensionality reduction, clustering, etc. The focus this semester will be on the mathematical foundations of these topics. Required Materials: Technical Requirements: This course assumes undergraduate-level knowledge of: 1) Probability (important) 2) Calculus and multivariable calculus 3) Linear algebra 4) Some analysis and discrete mathematics 5) Programming Furthermore, this course will assume that you have the maturity to carry out mathematical proofs. View Catalog Entry
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