This course extends what the student learned in Machine Learning I. A broader set of algorithms will be introduced. Students will have the opportunity to explore strategies for improving the performance of algorithms, such as feature selection and engineering, regularization, cross-validation, and parameter tuning. The latter part of the course will be devoted to introducing the basic concepts and structure for various neural networks.
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