Fall 2022

Machine Learning

Listed in: Computer Science, as COSC-247


Lee Spector (Section 01)


Machine Learning algorithms allow computers to be taught to perform tasks without being explicitly programmed. This course is an introduction to machine learning and data mining. The course will explore supervised, unsupervised, ensemble and reinforcement learning. Topics may include: decision tree learning, rule learning, neural networks, support vector machines, Bayesian learning, clustering, hidden Markov model learning, and/or deep learning. The material of this course has some overlap with that of Computer Science 241, but it is permissible to take both.

Requisite: COSC-211. Fall Semester: Professor Spector. 

How to handle overenrollment: priority to majors

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: Mathematical aptitude is essential.

COSC 247 - LEC

Section 01
Tu 02:30 PM - 03:50 PM SCCE A131
Th 02:30 PM - 03:50 PM SCCE A131

ISBN Title Publisher Author(s) Comment Book Store Price
Machine Learning with PyTorch and Scikit-Learn Packt Publishing Ltd., 2022 Sebastian Rashka, Yuxi (Hayden) Liu, and Vahid Mirjalili TBD


2023-24: Not offered
Other years: Offered in Fall 2022, Spring 2023