DS5220 (Supervised Machine Learning and Learning Theory) course reviews and ratings at Northeastern (NEU). Average rating 3.8/5. Compare professors with RateMyProfessor reviews.
Introduces supervised machine learning, which is the study and design of algorithms that enable computers/machines to learn from experience or data, given examples of data with a known outcome of interest. Offers a broad view of models and algorithms for supervised decision making. 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-world data sets. Requires proficiency in a programming language such as Python, R, or MATLAB.
Data updated October 2026.