ORIE 3741

Last Updated

  • Schedule of Classes - December 25, 2024 7:31PM EST
  • Course Catalog - December 25, 2024 7:07PM EST

ORIE 3741
Learning with Big Messy Data

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.

View Enrollment Information

Syllabi:

  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: ORIE 5741

  • 4 Credits GradeNoAud

  •  7644 ORIE 3741   LEC 001

  •  
    • TR
    • Jan 21 - May 6, 2025

    • Shafiee, S

  • Instruction Mode: In Person

  •  7645 ORIE 3741   DIS 201

  •  
    • M
    • Jan 21 - May 6, 2025

    • Shafiee, S

  • Instruction Mode: In Person

  •  7646 ORIE 3741   DIS 202

  •  
    • T
    • Jan 21 - May 6, 2025

    • Shafiee, S

  • Instruction Mode: In Person

  •  7647 ORIE 3741   DIS 203

  •  
    • W
    • Jan 21 - May 6, 2025

    • Shafiee, S

  • Instruction Mode: In Person

  •  7648 ORIE 3741   DIS 204

  •  
    • W
    • Jan 21 - May 6, 2025

    • Shafiee, S

  • Instruction Mode: In Person