Unstructured Data
Durham
Paul College of Business&Econ :: Decision Sciences
Credits: 3.0
Term: Spring 2021 - E-term IV (03/22/2021 - 05/13/2021)
Grade Mode: Letter Grading
Term: Spring 2021 - E-term IV (03/22/2021 - 05/13/2021)
Grade Mode: Letter Grading
Class Size:
24
CRN: 56158
CRN: 56158
This course introduces students to statistical and machine learning tools for modeling unstructured data; including emails, documents, text messages, and social media data. Topics to be covered include generalized linear models, decision trees for discrete data, k-means clustering, mixture models, and topic models. The course integrates numerous case studies to demonstrate practical approaches to analyzing large unstructured collections of data. Application areas include Marketing (Yelp and Trip Advisor reviews), Human Resources (healthcare plan analysis), Social media (Twitter, YouTube, and Instagram). The course delivery will be a mix of lectures, readings with discussion, and hands-on data analysis. Prereq: DS 805.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF
Times & Locations
Start Date | End Date | Days | Time | Location |
---|---|---|---|---|
3/22/2021 | 5/13/2021 | M | 5:40pm - 9:15pm | PBLANE 216 |