== Block-Seminar "Big Data & Scalable Machine Learning" ==

The Big Data & Scalable Machine Learning Seminar is an optional course in the module "Machine Learning 1-X" and is worth 3 LP (3 ECTS credits). 

In the general case, it is not possible to take the seminar as a standalone course. There are possible exceptions to this (e.g. it complements another ML or related course you are taking in parallel). In that case, a special request needs to be made. 

=== Termine und Informationen ===

||'''Erster Termin für Themenvergabe'''|| Monday 5 Nov 2018 from 10:00 to 11:00 in MA 004 ||
||'''Verantwortlich'''|| Prof. Dr. Klaus-Robert Müller ||
||'''Dozent:''' || Gregoire Montavon, gregoire.montavon@tu-berlin.de ||
||'''Sprache'''|| Englisch ||
||'''Anrechenbarkeit'''|| Wahlpflicht LV im Modul Machine Learning 1-X (Computer Science M.Sc.) ||
||'''ISIS''' || https://isis.tu-berlin.de/course/view.php?id=14498 ||

This seminar will cover a number of topics to scale machine learning, such as stochastic optimization methods, neural networks, distributed machine learning, and cover key applications such as learning from big data or real-time data analysis.

Students will read, understand, evaluate and present selected research papers. At the end of the semester, each student will present his/her topic in a 20 min talk (+ 5-10 min questions) in English. Students are required to attend the entire seminar.