About CS 5540 A

Provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (linear regression, logistic regression, neural networks, support vector machines, decision tree, ensemble models, random forest); unsupervised learning (clustering, dimensionality reduction, kernel methods); Also introduces deep learning such as convolutional neural networks and discusses recent applications.

Notes

Prereqs: STAT 2510 or 5510, and MATH 2522 or 2544; Colocated with CS 3540 A; Crosslisted with CSYS 5990 A; Total combined enrollment: 45; Open to Degree and PACE students

Syllabus Unavailable

Please contact the instructor for information about this course.

Important Dates

Note: These dates may not be accurate for select courses during the Summer Session.

Deadlines
Last Day to Add
Last Day to Drop
Last Day to Withdraw with 50% Refund
Last Day to Withdraw with 25% Refund
Last Day to Withdraw

Resources

There are no courses that meet this criteria.