Python Data Science Handbook
We're using this book for a "book club" at work. Doing 1 chapter every 2 weeks. Chapter 1 covers Jupyter, 2 covers numpy, 3 pandas, 4 matplotlib, and 5 machine learning. We just made it through the first 4 chapters and it lays a good foundation for those libraries. I suspect chapter 5 is the meatiest and most interesting chapter, which covers scikit-learn and machine learning techniques. It is a long chapter so we will spend a month on it.<p>I recommend combining this book with McKinney's Pandas book[1] and the author's excellent YouTube presentations at PyCon and PyData. Start with "Statistics for Hackers"[2] by Jake VanderPlas and then look for his others.<p>[1]: <a href="http://shop.oreilly.com/product/0636920050896.do" rel="nofollow">http://shop.oreilly.com/product/0636920050896.do</a><p>[2]: <a href="https://www.youtube.com/watch?v=Iq9DzN6mvYA" rel="nofollow">https://www.youtube.com/watch?v=Iq9DzN6mvYA</a>