PinnedPublished in:probabl.scikit-learn acceleration with GPUsOlivier explains how the Python array API in scikit-learn now enables 15x speed-ups in complex ML pipelines.Mar 10Mar 10
PinnedPublished in:probabl.Maintaining open source in the age of generative AI: Recommendations for maintainers and…Adrin & Cailean discuss how open source developers are dealing with rising AI-generated contributions.Feb 24Feb 24
Published in:probabl.The value of certifying your machine learning skills: A conversation with Dr. Fabian StephanyArturo Amor interviews Oxford’s Dr. Fabian Stephany about the value of ML skills and certifications.5d ago5d ago
Published in:probabl.scikit-learn acceleration with GPUs: A conversation with Dr. Andy TerrelGaël interviews Dr. Andy Terrel from NVIDIA about the benefits of GPU acceleration in scikit-learn for data scientists.Mar 17Mar 17
Published in:probabl.Current scikit-learn priorities at Probabl — March 2026 editionAdrin shares the priorities on the scikit-learn roadmap.Mar 11Mar 11
Published in:probabl.Skore Is Live: Track Your Data ScienceFrançois announces the launch of our new product Skore, what it can do, and who it is for.Mar 5Mar 5
Published in:probabl.For data scientists, by data scientists: Building the next generation of data science toolingGuillaume pinpoints frictions in data science workflows and explains his vision for overcoming them.Mar 3Mar 3
Published in:probabl.Beyond the hype: Charting a new direction for enterprise data science grounded in scienceFrançois shares his vision for tackling five major challenges in enterprise data science.Feb 17Feb 17
Published in:probabl.Demystifying table foundation models: The new models expanding the data scientist’s toolkitGaël demystifies table foundation models for non-technical readers.Feb 13Feb 13
