Data Science
DS 5230: Unsupervised Machine Learning and Data Mining
Lecture - 4 credits
ND
EI
IC
FQ
SI
AD
DD
ER
WF
WD
WI
EX
CE
- Introduces unsupervised machine learning and data mining, which is the process of discovering and summarizing patterns from large amounts of data, without examples of data with a known outcome of interest.
- Offers 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 data sets.
- Requires proficiency in a programming language such as Python, R, or MATLAB.
Introduces unsupervised machine learning and data mining, which is the process of discovering and summarizing patterns from large amounts of data, without examples of data with a known outcome of interest. Show more.