| |
Jan 05, 2025
|
|
|
|
|
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 2210 and CSCI 2300 ; or permission of instructor.
When Offered: Fall term annually.
Co-Listed: CSCI 6100 . Students cannot receive credit for both CSCI 4100 and CSCI 6100 .
Credit Hours: 4
Add to Portfolio (opens a new window)
|
|
