Opintojakso, lukuvuosi 2023–2024
DATA.ML.220
Advanced Deep Learning, 5 op
Tampereen yliopisto
- Kuvaus
- Suoritustavat
Opetusperiodit
Koodi
DATA.ML.220Opetuskieli
EnglishLukuvuodet
2021–2022, 2022–2023, 2023–2024Opintojakson taso
Advanced studiesArvosteluasteikko
General scale, 0-5Vastuuhenkilö
Responsible teacher:
Konstantinos DrososResponsible teacher:
Tuomas VirtanenResponsible organisation
Faculty of Information Technology and Communication Sciences 100 %
Coordinating organisation
Computing Sciences Studies 100 %
The contents of the course (lectures and lab sessions) can be summarized to the following bullet points:
- Advanced techniques for recurrent and convolutional neural networks
- Sequence-to-sequence modelling and attention mechanisms
- Reconstruction, denosing, and manifold learning with autoencoders
- Generative modelling with variational autoencoders and generative adversarial neural networks
- Adversarial training
- Self-supervised and representation learning
- Reinforcement learning
- Advanced deep learning applications (e.g. domain adaptation, machine translation, natural language processing, machine vision, and machine listening)
- Implementations in popular and open-source deep learning frameworks (e.g. PyTorch)
Osaamistavoitteet
Pakolliset esitiedot
Oppimateriaalit
Kokonaisuudet, joihin opintojakso kuuluu
Suoritustapa 1
The course will not be taught in the academic year 2021-2022
Kaikkien osuuksien suorittaminen on pakollista.
Exam
Tietoja ei opetusohjelmassa
Participation in teaching
Tietoja ei opetusohjelmassa