INTRODUCTION TO MACHINE LEARNING AND DATA MINING

Catalog description

This is an introduction to machine learning and data mining which covers the following topics with an emphasis on mathematical and statistical analysis in supervised learning. Topics include machine learning workflow, evaluation metrics, validation approaches, classification models including logistic regression, decision tree, boosting, random forest, support vector machines, neural networks, Bayesian methods, etc. If time allows, text mining and unsupervised learning topics will also be introduced in the course. Statistical software will be used. (Cross-listed with MATH 4450 , MATH 8456 , STAT 8456 )