Machine learning allows computers to find hidden insights without being explicitly programmed where to look or what to look for.

Thanks to the work of some dedicated developers, Python has one of the best machine learning platforms out there called SciKit Learn.

In this episode, Alexander Granfort is here to tell us about Scikit Learn and machine learning.

This is Talk Python to Me, number 31, recorded Friday, September 25th, 2015.

I'm a developer, in many senses of the word, because I make these applications,

but I also use these verbs to make this music.

I constructed line by line,

just like when I'm coding another software design. In both cases, it's about design patterns.

Anyone can get the job done. It's the execution that matters. I have many interests.

Sometimes it can flake. My creativity can usually be a benefit. Welcome to Talk Python to Me, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities.

This is your host, Michael Kennedy. Follow me on Twitter where I'm at M. Kennedy.

Keep up with the show and listen to past episodes at TalkPython.fm, and follow the show on Twitter via at Talk Python.

This episode is brought to you by Hired and Codship. Thank them for supporting the show on

Twitter via at Hired underscore HQ and at Cochip. Hey everyone. Thanks for listening today. Let me introduce

Alexander so we can get right to the interview.

Alexandra Granford is currently an assistant professor at Telecom Perestech and scientific consultant for the CEA Neurospin Brain Imaging Center.

His work is on statistical machine learning, signal and image processing optimization,

scientific computing and software engineering with a primary focus in brain functional imaging.

Before joining Telecom Paris Tech, he worked at the Martinez Center for Biomedical Imaging at Harvard in Boston.

He is also an active member for the Center for Data Science at Universite Paris SACLE.

Alexander, welcome to the show.

Thank you.

...