Jul 18, 2024  
Rensselaer Catalog 2015-2016 
Rensselaer Catalog 2015-2016 [Archived Catalog]

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CSCI 4100 - Machine Learning from Data

Introduction to the theory, algorithms, and applications of machine learning (supervised, reinforcement, and unsupervised) from data: What is learning? Is learning feasible? How can we do it? How can we do it well? The course offers a mix of theory, technique, and application with additional selected topics chosen from Pattern Recognition, Decision Trees, Neural Networks, RBF’s, Bayesian Learning, PAC Learning, Support Vector Machines, Gaussian processes, and Hidden Markov Models.

Prerequisites/Corequisites: Prerequisites: CSCI 2300; an advanced 4000-level algorithms-based CSCI or MATH course; familiarity with probability, linear algebra, and calculus.

When Offered: Fall term annually.

Cross Listed: CSCI 6100. Students cannot receive credit for both CSCI 4100 and CSCI 6100.

Credit Hours: 4

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