Outline
The lecture deals with theoretical and practical concepts from the fields of statistical learning and machine learning. The main focus is on predictive modeling. The tutorial applies these concepts and methods to real examples for illustration purposes.
Class meets twice per week in the building at Schellingstr. 3:
Mondays from 10–12 in R055, and Wednesdays from 12–14 in S007
| # |
Date |
Day |
Topic |
|---|---|---|---|
| 01 | 09.4. |
Mon. |
Intro. (F) |
| 02 | 11.4. |
Wed. |
Learning Theory (M) |
| 03 | 16.4. |
Mon. |
Exercise 1 (A) |
| 04 | 18.4. |
Wed. |
Learning Theory (M) |
| 05 | 23.4. |
Mon. |
CART (F) |
| 06 | 25.4. |
Wed. |
RF (F) |
| 07 | 30.4. |
Mon. |
Exercise 2 (A) |
| 08 | 02.5. |
Wed. |
TBA (M) |
| 09 | 07.5. |
Mon. |
Learning Theory (F) |
| 10 | 09.5. |
Wed. |
TBA (M) |
| 11 | 14.5. |
Mon. |
Exercise 3 (A) |
| 12 | 16.5. |
Wed. |
Performance Estimation & Resampling (F) |
| -- | 21.5. |
Mon. |
holiday |
| 13 | 23.5. |
Wed. |
Boosting a (F) |
| 14 | 28.5. |
Mon. |
Exercise 4 (A) |
| 15 | 30.5. |
Wed. |
Boosting b (F) |
| 16 | 04.6. |
Mon. |
ROC (F) |
| 17 | 06.6. |
Wed. |
TBA (M) |
| 18 | 11.6. |
Mon. |
TBA (M) |
| 19 |
13.6. |
Wed. |
Exercise 5 (A) |
| 20 | 18.6. |
Mon. |
GPs / Tuning / MBO (F) |
| -- | 20.6. |
Wed. |
cancelled |
| 21 | 25.6. |
Mon. |
Exercises 6 (A) |
| 22 | 27.6. |
Wed. | Variable / Feature Selection (F) |
| 23 |
02.7. | Mon. |
Exercises 7 / Q & A (A) |
| 24 | 04.7. | Wed. | Q & A |
- Trainer/in: Moritz Große Wentrup
- Trainer/in: Alexander Markham
- Trainer/in: Fabian Scheipl