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Lab Course Automated Machine Learning applied to Machine Learning Challenges

This Praktikum has the name Praktikum in der Arbeitsgruppe Automatisches Algorithmendesign: Automated Parameter Tuning in the HISinOne Campus Management system. If you want to participate, please enroll in the HISinOne to receive updates about the schedule.

Background

Machine Learning challenges, such as those hosted by Kaggle or ChaLearn serve three purposes:

  1. stimulate research in a scientific area
  2. showcase current state-of-the-art in a scientific area
  3. help companies solve their (Machine Learning) problems

Competitions are run since the beginning of the internet with the netflix price and the KDD cup being the most famous. Participating in a Machine Learning challenge presents the task of building a successful machine learning pipeline. Participants train their pipeline on a public training set and submit predictions for both a public and a private test set to the competition server. During the competition, a leaderbord based on the public test set is published. While it allows the user to assess the goodness of her pipeline, it allows for overfitting on this data.

This lab course gives you the chance to learn about automated machine learning and apply this knowledge in a machine learning competition.

Prerequisites

  • Lecture on Machine Learning or Statistical Pattern Recognition
  • Programming skills (python)

Dynamics

The lab course consists of two phases:

  1. introductory phase
  2. competition phase

For the competition phase, you have to give two short presentations:

  1. After two weeks of working on the competition: A brief overview of the competition, as well as the proposed steps to obtain good results.
  2. After the competition: A brief overview of the technical details.

Finally, each student has to hand in a 2-4-page report, explaining the solutions to the competitions in more detail.

Organization

  • Course type: Praktikum (6-ECTS)
  • Examination: Exercise sheet (25%), participation in the competition (25%), presentations (25%), final report (25%). The grading, as well as the type of examination may be updated until the first meeting.
  • Language: English

Schedule

Date Topic

Mo, 26.10.15
16.15-17.15
Room 00 009, Building 74

Introductory meeting

Mo, 30.11.2015
16.15-17.45
Room 00 009, Building 74
Kickoff phase 2

More dates will be announced during the lecture period.

Material

TBA

Contact

For questions, please send an email to Frank or Matthias.