Detailed Course Information |
Spring 2024 Semester
May 15, 2024 |
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| CS 2810 - Mathematics of Data Models |
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Studies the methods and ideas in linear algebra, multivariable calculus, and statistics that are most relevant for the practicing computer scientist doing machine learning, modeling, or hypothesis testing with data. Covers least squares regression, finding eigenvalues to predict a linear system’s behavior, performing gradient descent to fit a model to data, and performing t-tests and chi-square tests to determine whether differences between populations are significant. Includes applications to popular machine-learning methods, including Bayesian models and neural networks.
4.000 Credit hours 4.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture Computer Science Department Course Attributes: NUpath Analyzing/Using Data, NUpath Formal/Quant Reasoning, Computer&Info Sci Restrictions: Must be enrolled in one of the following Levels: Undergraduate Prerequisites: Undergraduate level CS 1800 Minimum Grade of D- and Undergraduate level CS 2500 Minimum Grade of D- |
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