Mar 23, 2019  
Rensselaer Catalog 2017-2018 
    
Rensselaer Catalog 2017-2018 [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. Students cannot receive credit for both CSCI 4100 and CSCI 6100.

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.

Credit Hours: 4



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