By: Northeastern University
Unsupervised machine learning and data mining is the process of discovering and summarizing patterns from large amounts of data, without examples of data with a known outcome of interest. This course is an introduction to unsupervised machine learning and data mining. Seeks to provides a broad view of models and algorithms for unsupervised data exploration. Discusses the methodological foundations behind the models and the algorithms, as well as issues of practical implementation and use, and techniques for assessing the performance. Includes a term project involving programming and/or work with real-life datasets. Prereq. CS5800 or EECE7205 (either may be taken concurrently); students should be proficient in programming languages such as Python, R, or Matlab.