Dive Into NLTK, Part I: Getting Started with NLTK
From the webpage:
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
Part VIII: Using External Maximum Entropy Modeling Libraries for Text Classification
Part IX: From Text Classification to Sentiment Analysis
Part X: Play With Word2Vec Models based on NLTK Corpus
My first post on this series, had only the first seven lessons listed.
There’s another reason for this update.
It appears that no second edition of Natural Language Processing with Python is likely to appear.
Sounds like an opportunity for the NLTK community to continue the work already started.
I don’t have the chops to contribute high quality code but would be willing to work with others on proofing/editing (that’s the part of book production readers rarely see).