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== Enrollment / Limited number of participants ==

If you intend to participate, please send an e-mail to lassner@tu-berlin.de with title "Seminar Machine Learning in the Sciences 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 first come/first serve basis. Please keep in mind that auditing students and Nebenhörer can only participate if less than 15 regular TU students register for the course (http://www.studsek.tu-berlin.de/menue/studierendenverwaltung/gast_und_nebenhoererschaft/parameter/en/).

Seminar Machine Learning in the Sciences

  • 1st meeting:

    2018-04-19 10:00 MAR 0.009

    Presentations:

    2018-07-19 10:00 - 16:00 MA 645

    Tutor:

    David Lassner lassner@tu-berlin.de

    Language

    English

Enrollment / Limited number of participants

If you intend to participate, please send an e-mail to lassner@tu-berlin.de with title "Seminar Machine Learning in the Sciences 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 first come/first serve basis. Please keep in mind that auditing students and Nebenhörer can only participate if less than 15 regular TU students register for the course (http://www.studsek.tu-berlin.de/menue/studierendenverwaltung/gast_und_nebenhoererschaft/parameter/en/).

IDA Wiki: Main/SS18_MLSCSE (last edited 2018-07-18 08:55:21 by DavidLassner)