On: Parsing English with 500 lines of Python (2013)

[shabadoop]

I was thinking about working through the NLTK book once I'm finished with Bishop's Pattern Recognition, would you be able to recommend an alternative?

[bra-ket → shabadoop]

check out Michael Collins's NLP course: https://www.coursera.org/course/nlangp

and notes: http://www.cs.columbia.edu/~mcollins/

he talks about averaged perceptron at the end (Lectures on generalized log-linear models - GLM http://www.cs.columbia.edu/~cs4705/)

perceptron tagger code (hw4 solution) can be found here https://github.com/emmadoraruth/Perceptron_Tagger.git

[vkhuc → shabadoop]

I think the book "Speech and Language Processing, 2nd Edition" from Prof. Daniel Jurafsky is very good http://www.amazon.com/Speech-Language-Processing-Daniel-Jura...

You can also check out the great online NLP course taught by the author and Prof. Chris Manning from Stanford: https://www.youtube.com/watch?v=nfoudtpBV68&list=PL6397E4B26...

[habeanf → shabadoop]

Dependency Parsing by Nivre et al was a good source for catching up from an NLP course to state-of-the-art http://www.amazon.com/Dependency-Synthesis-Lectures-Language...

[syllogism → habeanf]

It's still tough to recommend that, imo. If you could choose to beam it straight into your head? Yeah, go ahead. But working through a book takes a lot of time...It only gives you dependency parsing, and then you have to catch up on the last five years of dependency parsing.

[syllogism → shabadoop]

There's no alternative NLP book I can really recommend, no --- sorry. It's moving too fast, the books are going out of date too quickly.

You could try Hal Daume's blog, and Bob Carpenter's blog.

[sitkack → syllogism]

Here is a review [0] by Bob Carpenter of Foundations of Statistical Natural Language Processing [1].

[0] http://www.amazon.com/review/R2FUAZHGUOERHV

[1] http://www.amazon.com/Foundations-Statistical-Natural-Langua...

[syllogism → sitkack]

I know that book well. It's too dated.