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Differential Privacy Hackathon (€4500 Prize Pool and Flight to Community Meeting)
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Antigranular
Jun 12, 2024, 11:03:39 AM6/12/24
to opendp-c...@g.harvard.edu
Hello OpenDP Community,
I wanted to reach out to you about a differential privacy hackathon we are running at the moment here at Antigranular. The objective of the competition is to create machine learning models that predict heart conditions based on a synthetic dataset with a variety of clinical and demographic indicators. You can use OpenDP and other DP/ML libraries to compete for €4500 in prizes, plus we are also getting flight tickets for you to attend the OpenDP Community Meeting and TPDP 2024 if you get first place!
I have attached more details at the bottom of the email, and I look forward to seeing you on the leaderboard!!
Sincerely,
Competitions Team
I wanted to reach out to you about a differential privacy hackathon we are running at the moment here at Antigranular. The objective of the competition is to create machine learning models that predict heart conditions based on a synthetic dataset with a variety of clinical and demographic indicators. You can use OpenDP and other DP/ML libraries to compete for €4500 in prizes, plus we are also getting flight tickets for you to attend the OpenDP Community Meeting and TPDP 2024 if you get first place!
I have attached more details at the bottom of the email, and I look forward to seeing you on the leaderboard!!
Sincerely,
Competitions Team
Antigranular
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Problem description:
Utilize machine learning techniques to analyze the Heart Failure Prediction Dataset, containing synthetic data, and predict heart conditions with a high level of accuracy while maintaining patient privacy.
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Problem description:
Utilize machine learning techniques to analyze the Heart Failure Prediction Dataset, containing synthetic data, and predict heart conditions with a high level of accuracy while maintaining patient privacy.
Deadline for submissions:
Prizes:
A €4500 prize pool for tops spots on the leaderboard as well as prizes open for beginners, rewarding the best notebooks, lowest epsilon, or the best use of the OpenDP library. Finish first and you can win a trip to Boston to attend the OpenDP community meeting and the Theory and Practice of Differential Privacy (TPDP) 2024 Workshop.
Recommended libraries:
OpenDP, Opacus (PyTorch), TensorFlow Privacy, and Diffprivlib
Questions:
24th July, 2024
Prizes:
A €4500 prize pool for tops spots on the leaderboard as well as prizes open for beginners, rewarding the best notebooks, lowest epsilon, or the best use of the OpenDP library. Finish first and you can win a trip to Boston to attend the OpenDP community meeting and the Theory and Practice of Differential Privacy (TPDP) 2024 Workshop.
Recommended libraries:
OpenDP, Opacus (PyTorch), TensorFlow Privacy, and Diffprivlib
Questions:
If you have any questions or want advice from our team, drop us a message on Discord.
Competition link:
Competition link:
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