Unstructured Data
Durham
Paul College of Business&Econ :: Decision Sciences
Credits: 3.0
Term: Spring 2023 - E-term IV (03/20/2023 - 05/11/2023)
Grade Mode: Letter Grading
Term: Spring 2023 - E-term IV (03/20/2023 - 05/11/2023)
Grade Mode: Letter Grading
Class Size:
30
CRN: 54101
CRN: 54101
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 text mining, clustering, mixture models, deep learning, and topic models. The course integrates numerous applications to demonstrate practical approaches to analyzing large unstructured collections of data. Application areas include Marketing (Yelp and Trip Advisor reviews), Human Resources (health care plan analysis), Social Media (Twitter, YouTube, and Instagram). The course delivery will be a mix of lectures, readings/podcasts with discussion, and hands-on data analysis. Prereq: DS 805.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Burcu Eke Rubini
Times & Locations
Start Date | End Date | Days | Time | Location |
---|---|---|---|---|
3/20/2023 | 5/11/2023 | M | 5:40pm - 9:15pm | PBLANE 216 |