CS 5787

CS 5787

Course information provided by the Courses of Study 2020-2021.

Students will learn deep neural network fundamentals, including, but not limited to, feed-forward neural networks, convolutional neural networks, network architecture, optimization methods, practical issues, hardware concerns, recurrent neural networks, dataset acquisition, dataset bias, adversarial examples, current limitations of deep learning, and visualization techniques. We still study applications to problems in computer vision and to a lesser extent natural language processing and reinforcement learning. There will also be a session on understanding publications in deep learning, which is a critical skill in this fast moving area.

When Offered Spring.

Permission Note Enrollment limited to: Cornell Tech students.
Prerequisites/Corequisites Prerequisite: CS 5785/ECE 5414/ORIE 5750.

View Enrollment Information

Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion.

  • 3 Credits Stdnt Opt

  • 19189CS 5787  LEC 001

  • Instruction Mode: Online
    Enrollment limited to Ithaca CS MEng Only; Prerequisite: CS 4780. Instructor Permission Required. Class will be streamed from Cornell Tech to Ithaca Students.

  • 19188CS 5787  DIS 201

  • Instruction Mode: Online

Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion.

  • 3 Credits Stdnt Opt

  • 11708CS 5787  LEC 030

  • Instruction Mode: Online
    Taught in NYC. Enrollment Limited to Cornell Tech Students. Pre-Requisite: Students must have taken Applied Machine Learning.

  • 11709CS 5787  DIS 230

  • Instruction Mode: Online