[chipmonkey75]

My personal preference is to learn by doing, and the best place I've found for this particular task is Kaggle (http://www.kaggle.com). They have a variety of datasets and scored data mining tasks, great forums for every level, code examples, and even a set of tutorials specifically for learning scikit (one of Python's machine learning libraries): http://blog.kaggle.com/2015/04/08/new-video-series-introduct...

I don't have any relationship with Kaggle other than being a semi-active user, but I really dig what they've got going. For a step-by-step approach, start with their blog posts and work on their "Getting Started" competitions. Everything you need is there.

[apeeyush]

I created a github repo (https://github.com/apeeyush/machine-learning) to store and organize the codes I used in Kaggle contests (mainly knowledge contests). Recently, I have participated in some vision and CTR prediction contests as well but could not update them here since the code is still very hacky. Will really appreciate any contribution from the community.

[craigching]

That's a nice repository, thanks for sharing! I'll be combing through that as I make the transition from R to Python ;)