ORIE 5741
Last Updated
- Schedule of Classes - November 16, 2024 7:33PM EST
- Course Catalog - November 16, 2024 7:07PM EST
Classes
ORIE 5741
Course Description
Course information provided by the Courses of Study 2024-2025.
Modern data sets, whether collected by scientists, engineers, medical researchers, government, financial firms, social networks, or software companies, are often big, messy, and extremely useful. This course addresses scalable robust methods for learning from big messy data. We'll cover techniques for learning with data that is messy --- consisting of real numbers, integers, booleans, categoricals, ordinals, graphs, text, sets, and more, with missing entries and with outliers --- and that is big --- which means we can only use algorithms whose complexity scales linearly in the size of the data. We will cover techniques for cleaning data, supervised and unsupervised learning, finding similar items, model validation, and feature engineering.
When Offered Fall, Spring.
Prerequisites/Corequisites Prerequisite: MATH 2940, ENGRD 2700, ENGRD 2110/CS 2110, CS 2800 or equivalents.
Regular Academic Session. Choose one lecture and one discussion. Combined with: ORIE 3741
-
Credits and Grading Basis
4 Credits GradeNoAud(Letter grades only (no audit))
-
Class Number & Section Details
-
Meeting Pattern
- TR
- Jan 21 - May 6, 2025
Instructors
Shafiee, S
-
Additional Information
Instruction Mode: In Person
Enrollment limited to: Operations Research and Information Engineering (ORIE) Master of Engineering (M.Eng.) students during pre-enroll, others may enroll during add/drop.
-
Class Number & Section Details
-
Meeting Pattern
- M
- Jan 21 - May 6, 2025
Instructors
Shafiee, S
-
Additional Information
Instruction Mode: In Person
Department Consent Required (Add)
-
Class Number & Section Details
-
Meeting Pattern
- T
- Jan 21 - May 6, 2025
Instructors
Shafiee, S
-
Additional Information
Instruction Mode: In Person
Department Consent Required (Add)
-
Class Number & Section Details
-
Meeting Pattern
- W
- Jan 21 - May 6, 2025
Instructors
Shafiee, S
-
Additional Information
Instruction Mode: In Person
Share
Or send this URL: