👷 Seminar on Machine Learning, Information Retrieval, and Scientific Visualization
doc. RNDr. Petr Sojka, Ph.D.
👷 Seminar on Machine Learning, Information Retrieval, and Scientific Visualization

News

  • From this term on, the course is a regular research seminar in the stated researched areas. It is mandatory that enrolled student has a presentation on a research topic during the term. Topics of presentations are those focused primarily (but not necessarily) by the  Math Information Retrieval@FI group: machine learning, information retrieval, representation learning, and scientific visualization.
  • There is a discussion group with official course information and a communication channel, in addition to the course outline below: watch both frequently!

Topics and Course Outline

Week 1

Join us at A502 the Faculty of Informatics MU on February 16th at 10 AM (CET) (or cesnet.zoom.us/my/sojka).

  1. 10:00 Class introduction, warm-up round-up discussion (expectation, topics/expertise/background, suggested presentations, and readings). Bring your research presentation offers and ideas to present, read, study, and discuss!
  2. 10:20 Principles of research communication and scientific work, Reading a scientific paper. Put readers in your place!
    Specifics of CS research and doctoral studies and their evaluation at FI MU: CS conference rankings
  3. 10:30 Importance of "selling the ideas and work", picking the right topics and questions, researching "big issues", picking the right publication forums (in CS and NLP), and h-index as a measure of impact. The danger of Tyranny of metrics.
  4. 10:40 Motivating video: DEK's advice to young students.
  5. 10:45 Preparation of schedule of talks for this term, topics to cover.
  6. 11:10 Varia, socializing (team builder wanted!), lunch.


Week 2  TBA

Join us in room A502 at FI MU on February 23rd at 10 AM (CET).

Minipresentations of thesis topics of Master's students enrolled in the course.

Kapitola obsahuje:
1
Studijní text
Učitel doporučuje studovat od 18. 2. 2023 do 23. 2. 2023.

Week 3 – Individual work and consultations on research questions and project


Week 4 – Jakub Ryšavý

Join us in room A502 at FI MU on March 9 at 10 AM (CET) [or on Zoom.]

Kapitola obsahuje:
1
Obrázek
1
PDF
1
Video
1
Studijní text
Učitel doporučuje studovat od 2. 3. 2023 do 10. 3. 2023.

Week 5 – Katarína Grešová

Join us in room A502 at FI MU on March 16 at 10 AM (CET) [or on Zoom.]

Kapitola obsahuje:
1
PDF
1
Video
1
Studijní text
Učitel doporučuje studovat od 10. 3. 2023 do 18. 3. 2023.

Week 6 – Dávid Meluš

Join us in room A502 at FI MU on March 23 at 10 AM (CET) [or on Zoom.]

Kapitola obsahuje:
1
PDF
1
Video
1
Studijní text
Učitel doporučuje studovat od 16. 3. 2023 do 24. 3. 2023.

Week 7 – Michal Štefánik et al.

Join us in room A502 at FI MU on March 30 at 10 AM (CET) [or on Zoom.]

Kapitola obsahuje:
1
Studijní text
Učitel doporučuje studovat od 23. 3. 2023.

Week 8 – cancelled

Week 9 – Šárka Ščavnická

Join us in room A502 at FI MU on April 13 at 10 AM (CET) [or on Zoom.]

Kapitola obsahuje:
1
PDF
1
Video
1
Studijní text
Učitel doporučuje studovat od 4. 4. 2023 do 13. 4. 2023.

Week 10 – Marek Kadlčík

Join us in room A502 at FI MU on April 20 at 10 AM (CET) [or on Zoom.]

Kapitola obsahuje:
1
Obrázek
1
PDF
1
Video
1
Studijní text
Učitel doporučuje studovat od 13. 4. 2023.

Week 11 – no teaching

Week 12 – David Čechák

Join us in room A502 at FI MU on May 5 at 10 AM (CET) [or on Zoom.]

Kapitola obsahuje:
1
PDF
1
Video
1
Studijní text
Učitel doporučuje studovat od 27. 4. 2023 do 5. 5. 2023.

Week 13 – no teaching (MUNI Day)


Week 14 – Michal Štefánik, Marek Kadlčík

Join us in room A502 at FI MU on May 18th at 10 AM (CET) [or on Zoom.]

Kapitola obsahuje:
1
Studijní text
Nepovinná kapitola. Učitel doporučuje studovat od 11. 5. 2023 do 19. 5. 2023.


Tips for readings, discussions, and presentation preparations:

  1. Top2Vec towardsdatascience.com/top2vec-new-way-of-topic-modelling 
  2. How to speak by Patrick Winston (youtube video)

Žákovi, který se hrozil chyb, Mistr řekl: "Ti, kdo nedělají chyby, chybují nejvíc ze všech – nepokoušejí se o nic nového." Anthony de Mello: O cestě

To a student who was in danger, the Master said: "Those who do not make mistakes most of all – they do not try anything new." Anthony de Mello

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