Neural Networks: Theory and Implementation (NNTI, Winter 2022/2023)

This is is the version for CS, systems engineering, wirtschaftsinformatik, etc. No CoLi students permitted in this edition. The corresponding LSF entry .

Important: due to a lack of a sufficient number tutors, we might have to limit the number of participants to 150!

Starts: Tuesday, November 8st at 14:15

Location: large lecture hall mathematics, HS1 in E25

Exam: tbd

Registration: please register here by November 1st for participation. Registration for the exam has to be done separately. Please check LSF and the corresponding deadline.

Tutorials:

There will be six tutorials groups. Details to follow.

Outline:

  1. Linear Algebra and Principal Component Analysis (PCA)
  2. Numerical Computation
  3. Machine Learning Basics
  4. Deep Feedforwad Neural Networks
  5. Regularization for Deep Learning
  6. Optimization for Deep Learning
  7. Convolutional Neural Networks
  8. Sequence Modelling: Recurrent and Recursive Neural Networks

Text Books:

Neural Networks and Deep Learning by Charu C. Aggarwal

Deep Learning by Aaron Courville, Ian Goodfellow, Joshua Bengio