Deep Learning Hackathon

→ Europe/Berlin
Klemperer-Saal (Sächsische Landes- und Universitätsbibliothek)

Klemperer-Saal

Sächsische Landes- und Universitätsbibliothek

Zellescher Weg 18 01069 Dresden Germany https://www.slub-dresden.de/en/directions/
Peter Steinbach, Reni Schimmel
Description

The Dresden Deep Learning Hackathon ( #d3hack2019 ) is meant to bring together machine learning experts and scientific practitioners. Teams of 2-4 scientists can apply for the hackathon given a scientific problem they want to solve with machine learning. Upon approval, they will be assisted by one or two machine learning experts for 5 days consecutively! This effort is meant to give your team a head-start and potentially create an end-to-end machine learning solution for your science. The teams are motivated to publish a scientific paper about the hackathon efforts at dedicated conferences or in established journals - at best jointly with their mentors - after the hackathon. A win-win situation for all parties involved.

Participants of d3hack2019

If you are interested, we have compiled an overview of our teams and our mentors. Without them, there would be no hackathon at all.

Registration

The workshop admission fee per participant is €140 to cover room rent at the venue and consumables such food and drinks. Please sign up only if you have received approval during the call-for-applications process. Upon registration, we will send you an invoice with the bank credentials and all required details.

During the Hackathon

Accomodation

We will not reserve any hotel rooms on your behalf. Please book any accomodation on your own. We have prepared a accomodation page on this website, that lists some hotel options near and far from the venue.

Resources

We offer powerful compute resources at the TU Dresden as well as in the AWS cloud. Participants are henceforth only required to bring their laptops. If you have security concerns regarding your data, you can also work on your hardware at home while being mentored in Dresden. Contact us for details and recipes.

We recommend you to use jupyter notebooks either on the TU Dresden HPC cluster Taurus or in the AWS cloud EC2. Further details on how to use either will provided in this git repository.

Family Friendly Work

We strive to provide a family friendly environment at the hackathon. At this point, we cannot promise to provide full day child care for those who need it. Please contact us in case not having child care prevents you from attending. We encourage all participants to respect family friendly working hours from 9am - 3.30pm. As we know that hackathons tend to be work intensive, we will prepare a kids corner. This way, parents can bring their children to the hackathon if needed.

Code of Conduct

We ask all those present at the hackathon to align their participation to the Dresden Code of Conduct. We will appoint one male and one female representative to be in charge as a contact person in case violations occur.

Thank you to our Sponsors

We would like to express our deepest gratitude to all partners and sponsors that contribute(d) to our workshop:

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