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May 16, 2024
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ITCS 5156 - Applied Machine Learning
Explores the components of machine learning prediction functions for classification and regression with an emphasis on practical applications. Topics include: fundamental concepts, such as training, validation, overfitting, and error rates. Also introduces commonly-used machine learning algorithms, such as decision trees, naive Bayes, neural networks and random forests. Covers the complete machine learning pipeline, including data collection, feature creation, algorithms, and evaluation.
Credit Hours: (3)
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