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Data science instrumenting social media for advertising is responsible for todays politics

To my friends developing data science for the social media, marketing, and advertising industries,

It is time to accept that we have our share of responsibility in the outcome of the US elections and the vote on Brexit. We are not creating the society that we would like. Facebook, Twitter ...

Unison 2.48 binaries for ARM

I have built static binaries of Unision 2.48 for ARM and x86 64bits

Better Python compressed persistence in joblib

New persistence in joblib enables low-overhead storage of big data contained in arbitrary objects

Of software and Science. Reproducible science: what, why, and how

At MLOSS 15 we brainstormed on reproducible science, discussing why we care about software in computer science. Here is a summary blending notes from the discussions with my opinion.

“Without engineering, science is not more than philosophy”    —   the community

How do we enable better Science? Why do we do software ...

Nilearn 0.2: more powerful machine learning for neuroimaging

After 6 months of efforts, We just released version 0.2 of nilearn, dedicated to making machine learning in neuroimaging easier and more powerful.

This release integrates the features of the july sprint, and more.

Highlights

Better documentation ...

Job offer: data crunching brain functional connectivity for biomarkers

My research group is looking to fill a post-doc position on learning biomarkers from functional connectivity.

Scientific context

The challenge is to use resting-state fMRI at the level of a population to understand how intrinsic functional connectivity captures pathologies and other cognitive phenotypes. Rest fMRI is a promising tool for ...

MLOSS 2015: wising up to building open-source machine learning

Note

The 2015 edition of the machine learning open source software (MLOSS) workshop was full of very mature discussions that I strive to report here.

I give links to the videos. Some machine-learning researchers have great thoughts about growing communities of coders, about code as a process and a deliverable ...

Nilearn sprint: hacking neuroimaging machine learning

A couple of weeks ago, we had in Paris the second international nilearn sprint, dedicated to making machine learning in neuroimaging easier and more powerful.

It was such a fantastic experience, as nilearn is really shaping up as a simple yet powerful tool, and there is a lot of enthusiasm ...

Software for reproducible science: let’s not have a misunderstanding

Note

tl;dr: Reproducibilty is a noble cause and scientific software a promising vessel. But excess of reproducibility can be at odds with the housekeeping required for good software engineering. Code that “just works” should not be taken for granted.

This post advocates for a progressive consolidation effort of scientific ...

MLOSS: machine learning open source software workshop @ ICML 2015

Note

This year again we will have an exciting workshop on the leading-edge machine-learning open-source software. This subject is central to many, because software is how we propagate, reuse, and apply progress in machine learning.

Want to present a project? The deadline for the call for papers is Apr 28th ...