What a wonderful thing -- this book looks fantastic, but the approach to making it really takes the cake. I really hope interactive notebooks (iPython based or otherwise) and multiple authors collaborating on Github will become widespread.
They are covered near the end of the book. It should be enough to familarize yourself with and understand the basic concepts of MCMC. Anything more in-depth will require a strong mathematical background.
BTW : There are probably a ton of books that cover MCMC out there - that's just one I liked and which is freely downloadable.
Check inside title page, make sure you get 3rd printing of Murphy's: http://www.cs.ubc.ca/~murphyk/MLbook/errata.html
PS. There a second edition of that book, but I've heard that the first edition is better, because the second edition added a different author and expanded the book.
On the other hand, the GP's assertion that there is seldom a need for using Bayesian methods is also unwarranted; they are the basis for so many machine learning algorithms in common use -- particle filters, for example.
Would you or anyone happen to know of a good book that discusses the derivation of various advanced probability distributions? It is quite frustrating that every ML or stats book I come across run through various distributions without giving the reader any sort of motivation or intuition behind them. Without that intuition how am I supposed to have any idea when to apply one vs another?
- Cauchy: the horizontal distance from the origin at which an arrow shot at a random angle from a point below the origin hits the x-axis
- Gamma: how long you have to wait for the nth event in a
I'm sure these must be books that I haven't read.
(your-virtualenv) ~/path/to/the/book/Chapter1_Introduction $ ipython notebook --pylab inline
This is the second time I've seen it in the last month, I noticed it in the documentation of a Python static blog generator, Nikola .
Run it with ipython --pprint though, so you get automatic pretty printing. I also recommend using the qtconsole plugin , as it is Much Nicer.
Basically, if you like bpython, this is better in every way I can think of. If you like the plain python REPL, give this a shot anyway. :) You may be pleasantly surprised.
I think there's a vim or emacs python extension that connects to an ipython kernel to run execute python snippets.
While I agree PDFs are antiquated, I still like them for casual, off-the-grid reading, and opening many different pages and printing to PDF is not feasible or easy to organize once on my iPad for reading. All the same, I'll check this out.
That said, this idea looks awesome. I'd still appreciate a pdf to supplement this, though :).
I really really like this. Can these python interactive books be constructed to show and run code snippets of different languages?
There are extensions for Cython, Octave and C too. And there's a generic mechanism for scripting languages (%%script), but that only captures stdout, rather than moving objects between different languages.
I would still like to read text parts on my Nook. How would one go about converting this to epub?
As an alternative, you can try watching about 90 minutes of lecture starting here:
but it will drop you right into the fray without much context.