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  • Coding.Waterkant 2022
  • Projects
    • KI.EL Racing Challenge
    • AI and Art
    • Detection of Important Genome Elements
    • Identifying Correct Arguments in Open Text Answers
    • Marine Munitions: Identifying Geo-Locations in Historical Documents
    • Predicting Stock Price Dynamics
    • Automated Feedback for Students' Argumentative Essays
    • Enabling Researchers to Automatically Code their Text Responses from Assessments
    • Improving Lung Imaging with AI
    • Natural Language Query in Applied Contexts
    • Visualizing Language Algorithms
  • Resources
    • Introduction to Hugging Face
    • ML Ops - Using AWS to Train to Your Models and Streamlit to Bring Them Into Production
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Coding.Waterkant 2022

Check out the already participating projects!

NextKI.EL Racing Challenge

Last updated 2 years ago

From June 7 to 10, 2022, and with support of the State Chancellery of Schleswig-Holstein, the Waterkant Festival and Kiel.AI will bring together machine learning and AI enthusiasts to push their machine learning projects to the next level or to get expertise by joining others working on their projects - and all this in the unique atmosphere of the Waterkant Festival!

Register for the event ! Under the same link you also find more information on the participation.

The following projects are already participating in the event:

  • KI.EL Racing Challenge (Jake Petersen, opencampus.sh)

  • AI and Art (Vladimir Alexeev, OpenAI Embassador; Michael Haas, Freelance Digital Artist)

  • Detection of Important Genome Elements (Yiqing Wang and Dustin Hanke, University of Kiel)

  • Identifying Correct Arguments in Open Text Answers (Christian Mayer, University of Mannheim)

  • Marine Munitions: Identifying Geo-Locations in Historical Documents (Simon Van der Wulp and Juan Veliz, north.io)

  • Predicting Stock Price Dynamics (Jonas Mielck, University of Kiel and stackOcean GmbH)

  • Automated Feedback for Students' Argumentative Essays (Thorben Jansen and Nils-Jonathan Schaller, IPN Kiel)

  • Enabling Researchers to Automatically Code their Text Responses from Assessments (Fabian Zehner and Nico Andersen, DIPF Frankfurt)

  • Improving Lung Imaging with AI (Niklas Koser and Claus Glüer, University of Kiel)

  • Natural Language Query in Applied Contexts (Lennart Büttner, Sourceboat GmbH & Co. KG)

  • Visualizing Language Algorithms (Lena Krüger, Muthesius University of Fine Arts and Design)

HERE