Welcome to EE546 Recurrent Neural Networks

EE546 has a pre-requisite course! You should have taken EE541 or CENG623 (or any similar introductory deep learning course, with the consent of the instructor).

EE546 will cover various concepts related to recurrent neural networks (RNNs) in artificial intelligence. The course starts with an overview of sequence models, and continues with details on training RNNs. By introducing different recurrent architectural models from gated units to transformer networks, the course covers all fundamental concepts related to sequence learning in artificial intelligence.

  • Homework: %10
  • Midterm: %20
  • Final: %30
  • Project: %40
    • %16 online Presentation
    • %24 Project Report)
    • An RNN training practice using MATLAB or Python (and using a deep learning library of your choice)
    • (Python/PyTorch is advised)

See you on Fridays, 18:30
The link to our lectures is here: Zoom Link:
Meeting ID: 894 0457 6748
Passcode: 2iYtHr

This is a recurrent meeting (i.e. we will always use this link, even after the breaks)