Data Science
DS 5220: Supervised Machine Learning and Learning Theory
Lecture - 4 credits
ND
EI
IC
FQ
SI
AD
DD
ER
WF
WD
WI
EX
CE
- 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.
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. Show more.