CS 5787

CS 5787

Course information provided by the Courses of Study 2019-2020.

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.

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Enrollment Information
Syllabi: 1 available
  •   Regular Academic Session.  Choose one lecture and one discussion.

  • 3 Credits Stdnt Opt

  • 12677CS 5787  LEC 001

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

  • 12678CS 5787  DIS 201