Fall 2023
INF 397 Research in Information Studies: Introduction to Machine Learning / Statistical Analysis and Learning
Cross-listing of P A 397C, hosted by the LBJ School of Public Affairs.
DESCRIPTION
Large datasets are increasingly becoming available across many sectors such as healthcare, energy, and online markets. This course focuses on methods that allow “learning” from such datasets to uncover underlying relationships and patterns in the data, with a focus on predictive performance of various models that can be built to represent the underlying function generating the data. Topics to be covered: Linear Regression, Classification, Resampling Methods, Linear Model Selection and Regularization, Tree-Based Methods, Support Vector Machines, Unsupervised Learning (Clustering).
PREREQUISITES
Graduate standing.
RESTRICTIONS
Restricted to graduate students in the School of Information through registration periods 1 and 2. Outside students will be permitted to join our waitlists beginning with registration period 3.