Machine Learning

Catalog description

This course provides students with a broad introduction to machine learning, datamining, and statistical pattern recognition. Students will study data exploration, decision-tree, K-nearst neighborhoods, linear regression, logistic regression, support vector machines, neural networks, ensemble learning, clustering, dimensionality reduction, and model evaluations. Students will be required to build predictive models based on machine algorithms.