Dive Into NLTK

Dive Into NLTK Part I: Getting Started with NLTK

From the post:

NLTK is the most famous Python Natural Language Processing Toolkit, here I will give a detail tutorial about NLTK. This is the first article in a series where I will write everything about NLTK with Python, especially about text mining and text analysis online.

This is the first article in the series “Dive Into NLTK”, here is an index of all the articles in the series that have been published to date:

Part I: Getting Started with NLTK (this article)
Part II: Sentence Tokenize and Word Tokenize
Part III: Part-Of-Speech Tagging and POS Tagger
Part IV: Stemming and Lemmatization
Part V: Using Stanford Text Analysis Tools in Python
Part VI: Add Stanford Word Segmenter Interface for Python NLTK
Part VII: A Preliminary Study on Text Classification

Kudos for the refreshed index at the start of each post. Ease of navigation is a plus!

Have you considered subjecting your “usual” reading to NLTK? That is rather than analyzing a large corpus, what about the next CS article you are meaning to read?

The most I have done so far is to build concordances for standard drafts, mostly to catch bad keyword usage and misspelling. There is a lot more that could be done. Suggestions?

Enjoy this series!

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