Data Mining & Pred Modeling
Credits: 3.0
Term: Fall 2019 - E-term II (10/14/2019 - 12/10/2019)
Grade Mode: Letter Grading
Term: Fall 2019 - E-term II (10/14/2019 - 12/10/2019)
Grade Mode: Letter Grading
Class Size:
30
CRN: 15984
CRN: 15984
In this class, students will learn foundations of practical machine learning: upon completion, students will be able to understand and apply supervised and unsupervised learning in Python to build predictive models on real world datasets. Techniques covered include (but not limited to): preprocessing, dimensionality reduction, clustering, feature engineering and model evaluation. Models covered include: generalized linear models, tree-based models, bayesian models, support vector machines, and neural networks. All learning objectives are achieved through active application of these techniques to real world datasets. Prereq: DATA 800; DATA 820 Pre- or Coreq: DATA 821.
Mutual Exclusion : ADMN 872
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Times & Locations
Start Date | End Date | Days | Time | Location |
---|---|---|---|---|
10/14/2019 | 12/10/2019 | Hours Arranged | ONLINE |