Using naive Bayes to predict movie review sentiment

wyldfire · on March 20, 2015

Aside: are there any good open/online resources for learning about bayesian reasoning, NLP, machine learning or similar topics?

I've read "Probabilistic Programming & Bayesian Methods for Hackers" but it didn't feel like it explained enough of the concepts. I'd love something like an undergraduate curriculum/text if someone could recommend one.

markovbling · on March 20, 2015

If you want a thorough explanation of concepts (as opposed to the 'black box' 'use this library' approach taken by many tutorials I've seen) then I highly recommend John Foreman's (Data Scientist at MailChimp) book "Data Smart".

He implements algorithms on practical problems in Excel. I know that may sound off-putting but it's so much easier to visualise what's going on when you can see vectors of data change in a spreadsheet compared to trying to debug arrays in a more general programming language.

What led me to John - something I heard about here actually - was his blog called 'Analytics Made Skeezy' where he creates fictional 'drug dealer' GTA style examples such as "Forecasting Made Skeezy: Projecting Meth Demand using Exponential Smoothing"

http://analyticsmadeskeezy.com/blog/

I have no affiliation with John, just liked the blog enough to order his book and the book was excellent too

Good luck! :)

Pandabob · on March 20, 2015

I've often seen "An introduction to statistical learning" [1] and "Elements of statistical learning" [2] cited as good resources for statistical inference and machine learning. The former is more of an undergrad text, while the latter seems to be aimed at graduate students. Both books are available free online.

[1]: http://www-bcf.usc.edu/~gareth/ISL/ [2]: http://statweb.stanford.edu/~tibs/ElemStatLearn/

aet · on March 20, 2015

I think these texts take the "frequentist" view (primarily), but would still recommend 2 highly

kevcampb · on March 20, 2015

Information Theory, Inference, and Learning Algorithms by David MacKay, which is a very well known text. It's freely available online at:

http://www.inference.phy.cam.ac.uk/itprnn/book.html

parrao · on March 20, 2015

The text that we use at the undergrad level is AIMA[1] which is clear and expansive.

1. http://aima.cs.berkeley.edu/

aet · on March 20, 2015

David Barber's book Bayesian Reasoning and Machine Learning is available for free on his website.

wodenokoto · on March 20, 2015

Here's a direct link to the tutorial: https://www.dataquest.io/mission/24

I don't understand why it is in an iframe.