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== Beginners Workshop Machine Learning == == Advanced Workshop Machine Learning ==
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 || '''Organisation:''' || Seulki Yeom: seulki.yeom@tu-berlin.de, Philipp Seegerer: philipp.seegerer@campus.tu-berlin.de, David Lassner: lassner@tu-berlin.de ||  || '''Room:''' || 4th floor of MAR, Marchstr. 23 ||
 || '''Organisation:''' || Seulki Yeom: yeom@tu-berlin.de, Philipp Seegerer: philipp.seegerer@tu-berlin.de, David Lassner: lassner@tu-berlin.de ||
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 || '''Application deadline''' || July 31st, 2018 ||

== Enrollment / Limited number of participants ==

If you intend to participate, please send an e-mail to lassner@tu-berlin.de with title "Advanced 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/).

(temporary) Advanced Workshop Lecture topics are:

Monday
 * Introduction to Deep Neural Network

Tuesday
 * Medical Imaging, ConvNet, Interpretation (1/2)

Wednesday
 * Medical Imaging, ConvNet, Interpretation (2/2)

Thursday
 * Quantum Chemstry, SchNet (1/2)

Friday
 * Quantum Chemstry, SchNet (2/2)

Advanced Workshop Machine Learning

Enrollment / Limited number of participants

If you intend to participate, please send an e-mail to lassner@tu-berlin.de with title "Advanced 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/).

(temporary) Advanced Workshop Lecture topics are:

Monday

  • Introduction to Deep Neural Network

Tuesday

  • Medical Imaging, ConvNet, Interpretation (1/2)

Wednesday

  • Medical Imaging, ConvNet, Interpretation (2/2)

Thursday

  • Quantum Chemstry, SchNet (1/2)

Friday

  • Quantum Chemstry, SchNet (2/2)

IDA Wiki: Main/WS18_AdvancedWorkshop (last edited 2018-09-05 14:21:07 by PhilippSeegerer)