Introduction to Machine Learning. 3 credits, 3 contact hours

Catalog description

Prerequisites: CS 100 and ( CS 113 or CS 115 ) and ( MATH 333 or MATH 341 ) with a grade C or better. This is an introductory course to Machine Learning (ML). It consists of: (i) A smooth, example-based presentation of the fundamental notions of ML via simple algorithms and visualizable "toy" data sets. (ii) A tour of a selection of widely-used machine learning algorithms, including supervised, unsupervised, and reinforcement-based techniques, with applications on real data sets. The students are expected to implement basic algorithms and experiment with existing widely-used ML software libraries on real datasets. They will also gain exposure to the full development of an ML system via a course project.