CSE 4392 - Special Topics: Neural Networks and Deep Learning

Spring 2023
Lectures: MWF 10:00am-10:50am
Modality: Hybrid.
Classroom for face-to-face lectures: ERB 129.

• This is a hybrid class. Most lectures will be held ONLINE and not face-to-face. Students can attend every lecture live using Microsoft Teams.
• Starting Friday, February 17, all Friday lectures will be face-to-face.

This course offers an introduction to neural networks and deep learning. Topics include perceptrons, single-layer neural networks, multi-layer neural networks, Tensorflow and Keras, convolutional neural networks, transfer learning, deep learning methods for image classification, and sequential learning models for analyzing text. Auto-encoders and generative adversarial networks will be covered to some extent, as time permits. A strong programming and algorithmic background is assumed, as well as familiarity with linear algebra (vector and matrix operations). Prerequisites: Admitted into an Engineering Professional Program. C or better in each of the following: CSE 3318 (Algorithms), and CSE 3380 or MATH 3330 (Linear Algebra).

Links

• Course Information and Policies: You can treat this information as an unofficial version of the syllabus. The official version is posted on Canvas.

• Schedule and Lecture Slides

• Assignments

• Additional Resources