CS 5787

CS 5787

Course information provided by the 2025-2026 Catalog.

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.


Prerequisites/Corequisites Prerequisite: CS 5785, ECE 5414, ORIE 5750.

Permission Note Enrollment limited to: Cornell Tech students.

Last 4 Terms Offered 2025FA, 2024FA, 2023SP, 2022SP

When Offered Spring.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session. 

  • 3 Credits Stdnt Opt

  • 19409 CS 5787   LEC 030

    • TR
    • Aug 25 - Dec 8, 2025
    • Elor, H

  • Instruction Mode: In Person

    Enrollment limited to: Cornell Tech students.