CS 5785

CS 5785

Course information provided by the Courses of Study 2018-2019.

Learn and apply key concepts of modeling, analysis and validation from machine learning, data mining and signal processing to analyze and extract meaning from data. Implement algorithms and perform experiments on images, text, audio and mobile sensor measurements. Gain working knowledge of supervised and unsupervised techniques including classification, regression, clustering, feature selection, and dimensionality reduction.

When Offered Fall.

Permission Note Enrollment limited to: Cornell Tech students.
Prerequisites/Corequisites Prerequisite: CS 2800 or the equivalent plus basic familiarity with Matlab or Python, or permission of the instructor.

View Enrollment Information

Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Combined with: ECE 5414ORIE 5750

  • 3 Credits Stdnt Opt

  • 12791CS 5785  LEC 030

  • Taught in NYC. Enrollment limited to Cornell Tech students.

Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Combined with: ECE 5414ORIE 5750

  • 3 Credits Stdnt Opt

  • 17577CS 5785  LEC 031

  • Taught in NYC. Enrollment limited to Cornell Tech students.