2019 Fall
INDENG 142 001 - LEC 001
Introduction to Machine Learning and Data Analytics
Current Enrollment
Total Open Seats:
-8
Enrolled: 148
Waitlisted: 4
Capacity: 140
Waitlist Max: 20
Open Reserved Seats:
7 reserved for Operations Research and Management Science Majors with 5 or more Terms in Attendance`
6 reserved for Industrial Engineering and Operations Research: Majors and Graduate Students
Hours & Workload
3 hours of instructor presentation of course materials per week, 5 hours of outside work hours per week, and 1 hours of the exchange of opinions or questions on course material per week.
Other classes by Paul Grigas
Course Catalog Description
This course introduces students to key techniques in machine learning and data analytics through a diverse set of examples using real datasets from domains such as e-commerce, healthcare, social media, sports, the Internet, and more. Through these examples, exercises in R, and a comprehensive team project, students will gain experience understanding and applying techniques such as linear regression, logistic regression, classification and regression trees, random forests, boosting, text mining, data cleaning and manipulation, data visualization, network analysis, time series modeling, clustering, principal component analysis, regularization, and large-scale learning.
Rules & Requirements
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
Open Reserved Seats:
7 reserved for Operations Research and Management Science Majors with 5 or more Terms in Attendance`
6 reserved for Industrial Engineering and Operations Research: Majors and Graduate Students