Catalog Description:
- Introduction to Neural Networks
- Convolutional Neural Networks
- Training Neural Networks (activation functions, dropout, batch normalization)
- Word Embeddings
- Recurrent Neural Networks (RNNs, LSTMs, GRUs)
- Visualizing and Understanding Neural Networks (Deep Dream, Neural Style Transfer)
- Generative Models
- Advanced Deep Learning Models
Credits:
(3+0+0) 3 ECTS 10
Prerequisites:
Consent of Instructor. Students are expected to have a medium level knowledge of essential machine learning algorithms. Undergrads and grad students who are new to machine learning are encouraged to take CMPE462: Machine Learning course.
| Link | Year | Semester | Course Page | Instructor | Course Schedule | Lab Schedule | PS Schedule |
|---|---|---|---|---|---|---|---|
| view | 2021 | Spring | İnci Meliha Baytaş | FFF 234 | |||
| view | 2019 | Spring | Pınar Yanardağ | MMM 567 BM A5 | BM A5 | BM A5 | |||
| view | 2018 | Spring | Ethem Alpaydın | MMM 456 BM A6 | BM A6 | BM A6 | |||
| view | 2017 | Spring | Ethem Alpaydın | MMM 345 BM A5 | BM A5 | BM A5 |