CS 369 - Machine Learning

3 credit(s)
This course covers the basic concepts and techniques of Machine Learning from both the theoretical and practical perspectives. Topics include supervised learning, unsupervised learning, regression, and classification problems. Different machine learning algorithms such as decision trees, support vector machines, neural networks are covered. Implementation of machine learning algorithms will be discussed. Best practices for deploying and maintaining machine learning models in production are explored.
Prerequisite(s): CS 220P and M 144.
Laboratory fee.

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