MAT 420
Intro to Machine Learning · 3 credits · Spring 2027
Requirements
Corequisite: MAT 415 Non-Degree Students must seek approval from Math Department in Room N599
About this course
This course is an introduction to machine learning principles and techniques. The mathematics and applications of the following topics will be covered: generalization, point estimation, neural networks with an emphasis on the perceptron and generalizations, non-linear separation, dimension reduction and various supervised algorithms such as K-nearest neighbor. Time permitting, topic models and support vector machines will be discussed.
Seat status as of Oct 2, 6:33 PM ET. Seats can change between refreshes.
1500-LEC Regular
Tue/Thu · 3:00 PM - 4:40 PM
Fiterman 705
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