HN Theater @HNTheaterMonth

You might enjoy this talk "statistics for hackers" (in case statistics is not included in your data science knowledge): https://www.youtube.com/watch?v=Iq9DzN6mvYA

For structural beam analysis (ie, from mechanical and civil engineering) check out this textbook on the direct stiffness method: http://www.mastan2.com/textbook.html

Unfortunately, the accompanying code (MASTAN2) is not open source and runs in Matlab. Still, it's a decent first step if you want to move to full-on Finite Element methods, which require much heavier math (real analysis) to really grasp.

Statistics for Hackers by Jake Vanderplas https://www.youtube.com/watch?v=Iq9DzN6mvYA

A really nice intuitive intro to resampling methods.

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.

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.

[1]: http://shop.oreilly.com/product/0636920050896.do

[2]: https://www.youtube.com/watch?v=Iq9DzN6mvYA

⬐ nafizh

The notebooks say they are an excerpt from the book but some other place mentions you can read the book in its entirety in the posted link. So, the notebooks have all the content or part of the book?

⬐ pixelmonkey

To my knowledge, the notebooks include all, or almost entirely all, of the content in the print book. Jake mentions a few times in talks that the Notebooks are "compiled" into the O'Reilly book format. The nice thing about having the book as notebooks is you can literally "run the book as code" just by pointing Jupyter at that cloned repo.

⬐ neduma

Very good idea. Thinking of doing the same.

⬐ morenoh149

Can others attend your bookclub? I've been attending https://www.meetup.com/Math-and-Algorithm-Reading-Group/ over at buzzfeed HQ. This is right up the same alley.

Feynman's approach seems very reminiscent of Jake Vanderplas's Statistics for Hackers talk[0] as opposed to the purely theoretical physicist approach that the author notes at the end.

[0]: https://www.youtube.com/watch?v=Iq9DzN6mvYA