Catalog Entries |
Fall 2016
Apr 20, 2024 |
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| Select the Course Number to get further detail on the course. Select the desired Schedule Type to find available classes for the course. |
| CSCI 1420 - Machine Learning |
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We explore the theory and practice of statistical machine learning, focusing on computational methods for supervised and unsupervised data analysis. Specific topics include Bayesian and maximum likelihood parameter estimation, regularization and sparsity-promoting priors, kernel methods, the expectation maximization algorithm, and models for data with temporal or hierarchical structure. Applications to regression, categorization, clustering, and dimensionality reduction problems are illustrated by examples from vision, language, bioinformatics, and information retrieval. Prerequisites: CSCI 0040 or 0150 or 0180 or 0190; and CSCI 0450 or CSCI 1450 or APMA 1650 or MATH 1610; and CSCI 0530 or MATH 0520 or 0540; or instructor permission.
1.000 Credit hours 1.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Primary Meeting Computer Science Department |
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