Spring 2019: Artificial Intelligence

ICT Studies (Teleinformatyka), 3rd semester of MSc studies

Teachers:

The course is accessible via the AGH UPEL platform.

Project:

  • Calendar of Andrzej Kamisiński.
  • Obligatory milestones and/or meetings (arranging via e-mail):
    • up to 2019-03-25: formation of the project groups;
    • 1st meeting: up to 2019-03-29 (the selected topic and the main ideas behind the envisioned system);
    • 2nd meeting: up to 2019-04-12 (details of the proposed design);
    • 3rd meeting: up to 2019-05-10 (complete implementation of a prototype; the first evaluation results);
    • 4th meeting: up to 2019-05-31 (final evaluation results);
    • up to 2019-06-07: submission of the final report and all related source files;
    • Public presentations (5th meeting): 2019-06-14.

Lecture/seminar meetings: Mondays, lecture room 0.12/B-9

  • Group A: 8.00-9.30AM
  • Group B: 9.35-11.05AM

Topics of presentations and discussions (lectures/seminars):

  1. Introduction: lectures 1 and 2 (2019-03-11, 8.00-11.05): course rules, overview of artificial intelligence (AI) and machine learning (ML),
    classification of methods used in AI and ML (1) .
  2. Introduction: lectures 3 and 4 (2018-03-18, 8.00-11.05): classification of methods used in AI and ML (2), mathematical support for AI and ML.
  3. Seminar 1 (2019-04-01):
    • Group A: Statistics-based classification, presenters: PK & MS.
    • Group B: Regression Bayesian networks, presenters: KB, PD & PS.
  4. Seminar 2 (2019-04-08):
    • Group A: Overview of regression methods supported by machine learning, presenters: DK, ŁG & MZ.
    • Group B: Overview of activation functions used in neural networks, presenters: AF, KK & AW.
  5. Seminar 3 (2019-04-15):
    • Group B: Supervised learning in tensorflow, presenters: KC, JK & AZ.
  6. Seminar 4 (2019-04-29):
    • Group A: Various specific types of neural networks, presenters: MF, JW & RZ.
    • Group B: Convolutional and recurrent neural networks in tensorflow, presenters: BF, RK & DM.
  7. Seminar 6 (2019-05-06):
    • Group A: Optimization algorithms supporting learning in neural networks, presenters: AK & MK.
  8. Seminar 7 (2019-05-13):
    • Group A: MPNN (message-passing neural networks) architecture for network management, presenters: MU & KK.
    • Group B: Transfer learning in tensorflow, presenters: MŁ, MK & MP.
  9. Seminar 8 (2019-05-20):
    • Group A: Normalization methods in machine learning, presenters: AXML & JJZV.
    • Group B: Image-to-text generation with machine learning, presenters: JB, AG & DG.
  10. Seminar 9 (2019-05-27):
    • Group A: Reinforcement learning, presenters: AM, MZ & MS.
    • Group B: Geometric deep learning, presenters: VP & NB.
  11. Seminar 10 (2019-06-03):
    • Group A: Word embeddings, presenters: MT, DR & KA.
    • Group B: Feature selection, presenters: PS & BP.
  12. Seminar 11 (2019-06-10):
    • Group A: Convolutional and recurrent neural networks, presenters: EF, MR & ŁW.
    • Group B: Autoencoders, presenters: BO, JP & SF.

Calendar of Piotr Chołda: