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==== Skript ====		 ==== Literature ====
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==== Ergebnisse ==== ==== Results ====
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=== Technik === === Access to Matlab ===
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Die Server {{{ {bolero,pepino,fiesta}.cs.tu-berlin.de }}} sind von aussen per ssh zu erreichen. The servers {{{ {bolero,pepino,fiesta}.cs.tu-berlin.de }}} can be reached via ssh.

Praktikum Maschinelles Lernen und Datenanalyse

  • Schedule:

    Irregular, see calendar

    Room:

    FR 1505 (Mondays) und FR 6043 (Wednesday)

    Lecturer

    Prof. Dr. Klaus-Robert Müller

    Contact:

    Paul von Bünau

    Module:

    M.Sc. Module Praktikum Maschinelles Lernen und Datenanalyse

The aim of this lab course is to practice the process of explorative data analysis and understand the main algorithms. The focus is on dimensionality reduction, clustering, classification and regression. For each assignment, a number of algorithms have to be implemented (in Matlab) and analyzed in experiments on real or synthetic data. Taking the Matlab course and the Machine Learning lecture is highly recommended but not a formal prerequisite.

The lab course consists of two parts: a lecture (Mondays at 10.15am), which is held only when a new assignment is handed out, and a consultation on Wednesdays (10.15am) in all following weeks. Please have a look at the calendar for the exact schedule.

Please register in the google group to receive announcements and ask questions.

More information can be found in the german Informationsblatt.

Schedule

See calendar

Material

Literature

Lecture notes (as of April 2010)

Results

Matrikelnr.

Blatt 1

Blatt 2

Blatt 3

Blatt 4

Blatt 5

Access to Matlab

The servers  {bolero,pepino,fiesta}.cs.tu-berlin.de  can be reached via ssh.

IDA Wiki: Main/SS11_MLPraktikum (last edited 2011-09-07 13:01:52 by JanSaputraMueller)