Class Number: 1944
Description: Hours: Three hours lecture per week
Prerequisite: MATH 398
Description: Students will learn how to construct machine learning models using current data science programming languages. Topics will include regression, classification, nonparametric models, tree-based methods, deep learning models, and unsupervised learning techniques.
| Days | Time | Date Range | Location | Instructor |
|---|---|---|---|---|
| W | 06:00 PM - 08:50 PM | 08/27/2016 - 12/23/2016 | Ojai Hall 1964 | Matthew Wiers |
Status: Open
Session: Regular Academic Session
Units: 3.00
Class Components: Lecture
Career: Undergraduate
Start Date: 08/27/2016
End Date: 12/23/2016
Grading: Letter Grade
Class Availability
Information below is 24 hours old.Enrollment Total: 7
Available Seats: 13
Wait List Capacity: 5
Wait List Total: 0
Textbook / Other Materials
Textbook Status: Required
ISBN: 9781118727966
Title: Applied Predictive Analytics
Author: Abbott
Publish: John Wiley & Sons, Incorporate
Textbook Status: Required
ISBN: 9781118727935
Title: Applied Predictive Analytics: Principles and Techn
Author: Abbott
Publish: John Wiley & Sons, Incorporate
More textbook information including prices
Enrollment Information
- Upper Division
Notes
- Prerequisite course required. Consult CSUCI Catalog