Peekaboo

Yesterday a week-long scikit-learn coding sprint in Paris ended. And let me just say: a week is pretty long for a sprint. I think most of us were pretty exhausted in the end. But we put together a release candidate for 0.14 that Gael Varoquaux tagged last night. You can install it via:   pip install -U https://github.com/scikit-learn/scikit-learn/archive/0.14a1.zip There are also tarballs on github and binaries on sourceforge . If you want the most current version, you can check out the release branch on github: https://github.com/scikit-learn/scikit-learn/tree/0.14.X The full list of changes can be found in what's new . The purpose of  the release candidate is to give users a chance to give us feedback before the release. So please try it out and report back if you have any issues.

The ICML is now already over for two weeks, but I still wanted to write about my reading list, as there have been some quite interesting papers ( the proceedings are here ). Also, I haven't blogged in ages, for which I really have no excuse ;) There are three topics that I am particularly interested in, which got a lot of attention at this years ICML: Neural networks, feature expansion and kernel approximation, and Structured prediction.