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Automated Machine Learning

Winter Semester 2023/24 @kozaka93 @woznicak

Materials for courses conducted at the Faculty of Mathematics and Information Sciences, Warsaw University of Technology.

Notes

Links to interesting papers, books, recordings and more ➡️ here

Schedule

# Month-Day Lecture Lab Points
1 10-04 Course introduction ML
10-06
2 10-11 Intro to AutoML Pipelines
10-13
3 10-18 Frameworks, part I Pipelines, stacking, AutoGluon
10-20
4 10-25 Tunability I AutoGluon, hyperparameter optimization
10-27
5 11-08 Tunability II Work on HW1
11-03
6 11-15 Frameworks, part II Work on HW1
11-17
7 11-22 Presentation of HW1 Auto-Sklearn P* (10p)
11-24
8 11-29 Presentation of HW1 HW1 (40p)
12-01
9 12-06 MLJAR MLJAR
12-08
10 12-13 Meta-learning Work on HW2
12-15
11 12-20 Benchmarks
12-22
12 01-03 TabPFN TabPFN
01-05
13 01-10 Ensembles Work on HW2
01-12
14 01-17 Presentation of HW2 P* (10p)
01-19
15 01-24 Presentation of HW2 HW2 (40p)
01-26

General rules and course assessment

You can obtain up to 90 points during the term, which will be assigned according to the following list:

  • Homeworks (2 x 40 points)
  • Presentation (10 points)

The grades will be given according to the table:

Grade 3 3.5 4 4.5 5
Points (45, 54] (54, 63] (63, 72] (72, 81] (81, ∞)