This course is an introduction to Machine Learning, where students will learn both theory and application of this subject. Students will get exposure to a broad range of machine learning methods and hands-on practice with real data. Topics include linear and logistic regression, support vector machines, decision trees, dimensionality reduction, unsupervised learning, and neural networks.
Prerequisites: MTH 3300 and either MTH 3120 or MTH 4120.
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