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.

Prerequisite: CSCI 2210 and CSCI 2300

When Offered: FALL TERM ANNUALLY

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

Graded: GRADED

Credit Hours: 4

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RPI CONNECTIONS

ENGAGE

CSCI 4100 - Machine Learning from Data