(Part 2) Best natural language processing books according to redditors

I am self-teaching R right now. I am using the following books:

http://health.adelaide.edu.au/psychology/ccs/teaching/lsr/
http://www.routledge.com/articles/latent_variable_modeling_using_r_a_step-by-step_guide/
http://www.amazon.com/Handbook-Statistical-Analyses-Second-Edition/dp/1420079336
http://www.amazon.com/Data-Analysis-Graphics-Using-Example-Based/dp/0521762936
http://cran.r-project.org/doc/contrib/Lam-IntroductionToR_LHL.pdf

All can be found for free online either legally or pirate.

Currently browsing through Rajesh Rao's new book which seems great so far for an introductory work.

I learned from this book, I can recommend it:

https://www.amazon.com/Statistical-Methods-Recognition-Language-Communication/dp/0262100665/

Some of the next steps to learn would be:

• Taking the Fourier Transform (FFT) of the audio signal and extracting some features from that, like cepstral coefficients
  
• Hidden Markov Models
  
  I know CMU has some free audio data, might be a starting point:
  
  http://www.speech.cs.cmu.edu/databases/
  

You might be interested in looking into the subject of "aggregation functions" (e.g. https://www.amazon.com/Aggregation-Functions-Encyclopedia-Mathematics-Applications/dp/0521519268)

I feel you. There's not a lot of good resources for learning R. The best introduction I found was a slim little book called A First Course in Statistical Programming in R. I picked it up at an instructor's recommendation. What endeared me to it is that a lot of the worked-through exercises are classic CS problems (e.g. iterative square root finding) I was familiar with from Lisp/SICP, and I thought it was a nice, concise crash course on R's control flow.

There are a few example based approaches in R. Hadley's book on ggplot2 is worth a look, as is the online documentation. Both the book and the docs are more instructions on how to use ggplot2 than general guides for visualization, but the core ideas behind the grammar of graphics and ggplot2 are good starting points. As a bonus, the book is cheap and all the code in the examples is available online. Data Analysis and Graphics Using R is a much longer and more general introduction to experiments, statistics and graphics. If you are looking for an example heavy text to help you work through both stats and data visualization I recommend it. However it is long and somewhat expensive.

Tufte is certainly worth your time. I doubt there is a definitive guide. Data visualization is a bit like UI/UX design. There are a bunch of canonical rules which you shouldn't break until you know exactly what you are doing--then breaking them can be extremely valuable.

What? No...

I imagine you can use it just fine to do some aspects of biological research but "R is a free software environment for statistical computing and graphics." http://www.r-project.org/

Here's a book: http://www.amazon.com/Data-Analysis-Graphics-Using-Example-based/dp/0521861160

From reviews of previous edition: "The text includes a wealth of practical examples, drawn from a variety of practical applications which should be easily understood by the reader. The methods demonstrated are suitable for use in areas such as biology, social science, medicine and engineering. The core of the book is taken up with detailed discussion of regression methods which leads onto more advanced statistical concepts."
ISI Short Book Reviews

If you're interested in natural language processing, learning Prolog would be a great start. It's very different from most other languages, but its structure makes tokenizing, tagging, parsing, etc. super simple once you get comfortable with it. I used this book to learn Prolog in a class. It's written by a computational linguist (Covington). He also has another book specifically about NLP, but it is out of print and thus quite expensive.

Amazon has lots of used copies, that's where I got mine.

This one is also pretty good, and dead cheap!

Koehn's book on SMT is extremely approachable and gives you all the background you need to implement a pretty decent phrase-based SMT system from scratch. If you want to learn from an existing system, you can also look into Moses.