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.
At the request of a friend, I am putting up some of the posters that I recently presented at conferences.
Large-scale functional-connectivity graphical models for individual subjects using population prior.
This is a poster for our NIPS work
Multi-subject dictionary learning to segment an atlas of brain spontaneous activity …
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 …
