Stepping up as probabl's CSO to supercharge scikit-learn and its ecosystem

"I'm thrilled to announce that I'm stepping up as Probabl 's CSO (Chief Science Officer) to supercharge scikit-learn and its ecosystem, pursuing my dreams of tools that help go from data to impact. Scikit-learn, a central tool Scikit-learn is central to data-scientists' work: it is the most used machine-learning package. It has grown over more than a decade, supported by volunteers' time, donations, and grant funding, with a central role of Inria."

"Scikit-learn keeps growing because it enables crucial applications: machine-learning that can be easily adapted to a given application. This type of AI does not make the headlines, but it is central to the value brought by data science. It is used across the board to extract insights from data and automate business-specific processes, thus ensuring function and efficiency of a wide variety of activities. And scikit-learn is quietly but steadily advancing."

A leadership change positions Probabl to actively accelerate scikit-learn and its ecosystem toward greater impact. Scikit-learn remains the most-used machine-learning package, grown over a decade through volunteers, donations, grants, and Inria support. Continued adoption stems from its adaptable algorithms that extract insights and automate domain-specific processes across industries. Recent releases improved computational foundations (array API, GPU support), user interfaces (rich HTML), new models (HDBSCAN, temperature-scaling recalibration), and algorithmic speedups (release 1.8). Probabl raised seed funding, aligns founders with scikit-learn contributions, and is investing in features, releases, documentation, communication, training, and enterprise tooling.

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