> but there are plenty of jobs that don't require a PhD where ML knowledge is an asset.
Could you give me an example?
And where should I start? I found some courses on coursera, udacity, and a few https://github.com/open-source-society/computer-science-and-engineering
Also, this book seems interesting http://www.amazon.co.jp/Machine-Learning-Python-Techniques-Predictive/dp/1118961749/ref=sr_1_1?ie=UTF8&qid=1444086313&sr=8-1&keywords=machine+learning+python
A couple of the books you mentioned haven't been published yet. Honestly, the strength of scikit-learn is that it is really, really, really easy to, well, learn. It's so straightforward. If you can't figure out how to use sklearn from the many, many quality examples on the site and numerous blog posts out there (http://zacstewart.com/2014/08/05/pipelines-of-featureunions-of-pipelines.html helped me a ton learning Pipelines!), I'd suggest you have bigger fish to fry.
Ok, to show that I'm not a total meany, if you must have a book recommendation, check out Machine Learning in Python by Bowles. It's an intro to ML using sklearn:
http://www.amazon.com/Machine-Learning-Python-Techniques-Predictive/dp/1118961749