You're welcome to download and reuse the PDF from any of the
presentations that I have given:
https://www.slideshare.net/GaelVaroquaux/presentations
None of them is an unbiased comprehensive overview of scikit-learn (not
sure how much this possible).
Gaël
On Tue, Jun 13, 2017 at 08:55:15PM -0300
Hi Gael
Thanks for the work! We are grateful for the work that other people do in
providing these types of tutorials and introductions as they lower the
barrier of entry for new people to get into machine learning. We generally
don't include these in the official sklearn documentation, in no small
It's unclear to me what exactly you want to do with the classification
algorithm. Is your goal to take in a binary data matrix indicating the
presence of certain k-mers and predict whether the the present k-mers
indicate a susceptible or resistant genome? If so, then you need to convert
your sequen
Indeed, thank you, Gael!
My 2c, not thought through very thoroughly, is that although a "related
tutorials" would be great, it would be considerably more of a maintenance
burden than scikit-learn-contrib, because docs go staler faster than code.
We *could* force all code in the doc to be runnable
