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== Beginners Workshop Machine Learning == == Advanced Workshop Machine Learning ==
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 || '''Lecture time:''' || 8:45 - 12:00, 13:30 - 17:00 (approx.) ||
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 || '''Organisation:''' || Seulki Yeom: seulki.yeom@tu-berlin.de, Philipp Seegerer: philipp.seegerer@tu-berlin.de, David Lassner: lassner@tu-berlin.de ||  || '''Room:''' || MAR 4.063, 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 ||
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== Lecture Topics ==

Monday, Oct 1 2018:
 * Introduction to Deep Neural Networks

Tuesday, Oct 2 2018:
 * Deep Learning in Practice, Interpretation of Deep Neural Networks

Thursday, Oct 4 2018:
 * Medical Imaging, Convolutional Neural Networks

Friday, Oct 5 2018:
 * Deep Learning for Quantum Chemistry

Monday, Oct 8 2018:
 * Recap

== Organizational ==
 * You can register for the corresponding course on ISIS: https://isis.tu-berlin.de/course/view.php?id=13919
 * Please notify us if you are able to bring your own computer.

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/).

Lecture Topics

Monday, Oct 1 2018:

  • Introduction to Deep Neural Networks

Tuesday, Oct 2 2018:

  • Deep Learning in Practice, Interpretation of Deep Neural Networks

Thursday, Oct 4 2018:

  • Medical Imaging, Convolutional Neural Networks

Friday, Oct 5 2018:

  • Deep Learning for Quantum Chemistry

Monday, Oct 8 2018:

  • Recap

Organizational

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