Course Title
Machine Learning
Department
Credit Hrs
3
Grade Modes
Audit, Pass/Fail, Standard Letter
Course Description
This course introduces machine learning concepts such as unsupervised and semi-supervised learning, naive bayesian, decision trees/regression tree, K-means, K-NN, regression, SVM, neural networks. The associated training & operating algorithms are presented, including ensemble machine learning. Solutions for related problems such as classification, regression, anomaly detection, time series prediction, image-to-image, sequence-to-sequence, rule learning, Markov chain learning etc. Concepts used to prepare training datasets.
Prerequisite
Complete ALL of the following Courses:
- MATH3082
Complete ALL of the following Courses:
- CSE3007
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The Math and Computer Science Requirement courses must be passed with a C or better or have consent of instructor and advisor before enrolling in CSE 4066.