Machine Learning Basics

Abstract

This is a course in machine learning for big data. The emphasis will be on developing scalable/parallel algorithms for various machine learning tasks. In addition to lectures on background material by the instructor, the course will also have paper presentations by students. Topics covered are expected to be: regression, classification, clustering, dimensionality reduction, matrix completion, parallel programming, optimization, etc. A substantial portion of the course will focus on research projects, where students will choose a well defined research problem.