CS 707 Data and Web Science Seminar (FSS 2017)

The Data and Web Science seminar covers recent topics in data and web science. This term, the seminar focuses on machine learning libraries and platforms.

Organization

Goals

In this seminar, you will
  • explore and experiment with a popular machine learning platform of your choice,
  • solve a small, self-defined machine learning problem with this platform,
  • give an overview over the platform, your problem, and your solution.

Schedule

  • Register as described below
  • Attend the kickoff meeting Feb. 15th in our seminar room
  • Work individually throughout the semester: explore relevant literature; gain hands-on experience; select and solve a small, concrete machine learning problem; write a report; give a 3-minute flash presentation on your topic; give a 15-minute presentation on your topic, problem, and solution
  • Meet your advisor for guidance and feedback
  • For more information, have a look at the full schedule

Registration

Explore the list of topics below and select at least 3 topics of your preference. Send a ranked list of your selected topics via email to ywang(at)uni-mannheim.de until Feb. 09 Feb 13 (extended). We will confirm your registration immediately. The actual topic assignment takes place soon after the registration deadline and we will notify you via e-mail. Our goal is, of course, to assign to you to one of your preferred topics.

Topics

Notice that in order to successfully participate in this seminar, you need to have adequate programming experience and be comfortable with exploring new systems or interfaces. You can find tutorials and documents of the selected systems following the links below. 

Students are free to suggest alternative choices.

Resources

Datasets

 

 Giving talks / writing reports

  • "Giving conference talks", by Prof. Dr. Rainer Gemulla [pdf]
  • "Writing for Computer Science" by Justin Zobel