We just released skrub 0.2.0. This release markedly simplifies learning on complex dataframes.
The highlight of the release is the tabular_learner function, which facilitates creating pipelines that readily perform machine learning on dataframes, adding preprocessing to a scikit-learn compatible learner …
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Open-source efforts around scikit-learn at Inria are spinning off to a new enterprise, Probabl, in charge of sustainable development of a data-science commons.
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François Chollet rightfully said that people often underestimate the impact of scikit-learn. I give here a few illustrations to back his claim.
A few days ago, François Chollet (the creator of Keras, the library that that democratized deep learning) posted:
Indeed, scikit-learn continues to be the most popular machine …
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With the growth of scikit-learn and the wider PyData ecosystem, we want to recruit in the Inria scikit-learn team for a new role. Departing from our usual focus on excellence in algorithms, statistics, or code, we want to add to the team someone with some technical understanding, but an …
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An important acknowledgement for a different view of doing science: open, collaborative, and more than a proof of concept.
A few days ago, Loïc Estève, Alexandre Gramfort, Olivier Grisel, Bertrand Thirion, and myself received the “Académie des Sciences Inria prize for transfer”, for our contributions to the scikit-learn project …
We have just announced that a foundation will be supporting scikit-learn at Inria [1]: scikit-learn.fondation-inria.fr
This is an exciting turn for us, because it enables us to receive private funding. As a result, we will be able to have secure employment for some existing core …
Two weeks ago, we held a scikit-learn sprint in Austin and Paris. Here is a brief report, on progresses and challenges.
Several sprints
We actually held two sprint in Austin: one open sprint, at the scipy conference sprints, which was open to new contributors, and one core sprint, for more …
Two week ago, we held in Paris a large international sprint on scikit-learn. It was incredibly productive and fun, as always. We are still busy merging in the work, but I think that know is a good time to try to summarize the sprint.
We had a …
A week ago, the 2014 edition of the scikit-learn sprint was held in Paris. This was the third time that we held an internation sprint and it was hugely productive, and great fun, as always.
We had a mix of core contributors and newcomers, which …
We have just released the 0.15 version of scikit-learn. Hurray!! Thanks to all involved.
It’s been a while since the last release of scikit-learn. So a lot has happened. Exactly 2611 commits according my count. Quite clearly, we have more and more existing code …
I’d like to welcome the four students that were accepted for the GSoC this year:
Welcome to all of you. Your submissions were excellent, and you demonstrated a good will …
I have tagged and released the scikit-learn 0.14 release yesterday evening, after more than 6 months of heavy development from the team. I would like to give a quick overview of the highlights of this release in terms of features but also in term of performance. Indeed, the scikit-learn …
Yesterday, we released version 0.11 of the scikit-learn toolkit for machine learning in Python, and there was much rejoincing.
In the last 6 months, there have been many things happening with the scikit-learn. While I do not whish to give an exhaustive …
The scikit-learn got 3 students accepted for the Google summer of code.
Happy new year, every one. I have just released Joblib 0.6.0 beta. The highlights of the 0.6 release are a reworked enhanced pickler, and Python 3 support.
Many thanks go to the contributors to the 0.5 …
The NIPS conference: time for a sprint. The NIPS conference, one of the major conferences in machine learning, is hosted in Granada this year. I believe that it is the first time that it is hosted in Europe. As many of the scikit-learn developers are part of the wider NIPS …
Once again, we are looking for a junior developer to work on the scikit-learn. Below is the official job posting. As a personal remark, I would like to stress that this is a unique opportunity to be payed for two years to work on learning and improving the scientific Python …
Last week, I was at the Scipy conference in Austin. It was really great to see old friends, and Austin is such a nice place.
The Scipy conference was held in UT Austin’s conference center, which is a fantastic venue. This is the …
The scikit-learn is a Python module for machine learning. The project builds on the scientific and numerical tools of the scipy community to provide state-of-the-art data analysis tools. It is developed by a community of open source developers to which my research team (Parietal, INRIA) contributes a lot and is …
The scikit-learn team is organizing a sprint on April 1st (that next Friday). Join us in Paris, Boston, or on IRC!
With the rise of the data sciences, the scikit-learn, a BSD-licensed Python package for machine learning, is becoming an asset for more and more endeavors. Machine learning has traditionally …
