1776
Comment:
|
1859
|
Deletions are marked like this. | Additions are marked like this. |
Line 5: | Line 5: |
|| '''To:''' || Aug 02, 2019|| || '''Lecture time:''' || TBA || |
|| '''To:''' || Aug 09, 2019|| || '''Lecture time:''' || 8:00 - 18:00 || |
Line 27: | Line 27: |
Participation spots are mostly assigned on a random basis. Please keep in mind that auditing students and Nebenhörer can only participate if less than the maximum number of regular TU students register for the course (http://www.studsek.tu-berlin.de/menue/studierendenverwaltung/gast_und_nebenhoererschaft/parameter/en/). | Participation spots are mostly assigned on a random basis. Please keep in mind that auditing students and Nebenhörer can only participate if less than the maximum number of regular TU students register for the course (http://www.studsek.tu-berlin.de/menue/studierendenverwaltung/gast_und_nebenhoererschaft/parameter/en/). Your participation will be confirmed soon after the application deadline. |
Beginners Workshop Machine Learning
The workshop takes place during the semester break and is 2 weeks long.
From:
Jul 29, 2019
To:
Aug 09, 2019
Lecture time:
8:00 - 18:00
Exam:
Aug 19, 2019 (presumably)
Room:
TBA
Organisation:
Seulki Yeom: yeom@tu-berlin.de, Philipp Seegerer: philipp.seegerer@tu-berlin.de, David Lassner: lassner@tu-berlin.de
Language
English
Application deadline
June 01, 2019
Enrollment / Limited number of participants
If you intend to participate, please send an e-mail to yeom@tu-berlin.de or philipp.seegerer@tu-berlin.de with title "Beginners Workshop Enrollment" and this text:
Name: Your name Matr.Nr: Your student ID (Matrikelnummer) Degree: The degree you are enrolled in and want to use this course for. TU student: Yes/No (Are you a enrolled as a regular student at TU Berlin?) Other student: If you are not a regular student, please write your status. ML1: Yes/No (Did you take the course Machine Learning 1 at TU Berlin?) Other ML course: If you did not take ML1 at TU Berlin, please write if you took any equivalent course.
Participation spots are mostly assigned on a random basis. Please keep in mind that auditing students and Nebenhörer can only participate if less than the maximum number of regular TU students register for the course (http://www.studsek.tu-berlin.de/menue/studierendenverwaltung/gast_und_nebenhoererschaft/parameter/en/). Your participation will be confirmed soon after the application deadline.
Workshop topics include:
1. Math and Python recap
2. Machine learning basics
3. Clustering
4. Classical and linear methods
5. Bayesian learning
6. Support vector machines
7. Kernels
8. Neural networks