Sep 19, 2019  
Rensselaer Catalog 2018-2019 
    
Rensselaer Catalog 2018-2019 [Archived Catalog]

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CSCI 6100 - 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 it be done? How can it be done 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 4100. Students cannot receive credit for both CSCI 4100 and CSCI 6100.

Credit Hours: 4



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