Join the DIG4BIO Raman Transfer Learning Challenge!

We’re excited to announce the launch of an international coding competition on Kaggle! Participants will tackle a real-world transfer learning problem in spectroscopy, predicting the concentrations of glucose, acetate, and magnesium sulfate from Raman spectra — even across different instruments!

Why join?
– Work on a cutting-edge machine learning challenge rooted in bioprocessing and analytical chemistry.
– Access a unique dataset of 2,500+ Raman spectra from 8 different devices.
– Test your model’s ability to generalize across hardware — a crucial hurdle in real-world PAT (Process Analytical Technology) applications.
– Win one of three cash prizes: 1st – $750 | 2nd – $450 | 3rd – $300

• The competition is open now and runs for the next 3 months!
• Hosted on Kaggle | Backed by the EU-HORIZON Dig4Bio project and KIWI-biolab.
• Join the challenge, push the limits of domain adaptation, and contribute to the future of instrument-agnostic spectroscopy!
• https://lnkd.in/dk-qjcrr

hashtag#MachineLearning hashtag#Spectroscopy hashtag#TransferLearning hashtag#RamanChallenge hashtag#Dig4Bio hashtag#Bioprocessing hashtag#PAT hashtag#DataScience hashtag#KaggleCompetition hashtag#OpenScience