🚀 Excited to announce the release of skada v0.6.0! This new release brings important additions to the library and continued work to keep the ecosystem compatible with Sklearn!
Théo Gnassounou
@tgnassou.bsky.social
Ph.D. student in Machine Learning and Domain Adaptation for Neuroscience at Inria Saclay/ Mind. Website: https://tgnassou.github.io/ Skada: https://scikit-adaptation.github.io/
I'm thrilled to have been awarded the thesis prize by the SSFAM 🥳 Thank you to the jury for the recognition you've given me 🙏 A big thanks to @rflamary.bsky.social and Alex to supporting me in this PhD! I'm looking forward to present my work at CAp 2026 in Montpellier, see you there :)
Figure 1. Happy ML researcher and open source developer presenting his toolbox SKADA at PyData Paris. Congrats @tgnassou.bsky.social the presentation was awesome!
Skada Sprint Alert: Contribute to Domain Adaptation in Python 📖 Machine learning models often fail when the data distribution changes between training and testing. That’s where Domain Adaptation comes in — helping models stay reliable across domains.
🚀 I’m pleased to announce a new preprint! "SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities" 📢 Check it out & contribute! 📜 Paper: arxiv.org/abs/2407.11676 💻 Code: github.com/scikit-adapt...
🚀 Skada v0.4.0 is out! Skada is an open-source Python library built for domain adaptation (DA), helping machine learning models to adapt to distribution shifts. Github: github.com/scikit-adapt... Doc: scikit-adaptation.github.io DOI: doi.org/10.5281/zeno... Installation: `pip install skada`
