Deep dive into understanding human language with Python by Alyona Medelyan.
Abstract:
Whenever your data is text and you need to analyze it, you are likely to need Natural Language Processing algorithms that help make sense of human language. They will help you answer questions like: Who is the author of this text? What is his or her attitude? What is it about? What facts does it mention? Do I have similar texts like this one already? Where does it belong to?
This tutorial will cover several open-source Natural Language Processing Python libraries such as NLTK, Gensim and TextBlob, show you how they work and how you can use them effectively.
Level: Intermediate (knowledge of basic Python language features is assumed)
Pre-requisites: a Python environment with NLTK, Gensim and TextBlob already installed. Please make sure to run nltk.download() and install movie_reviews and stopwords (under Corpora), as well as POS model (under Models).
Code examples, data and slides from Alyona’s NLP tutorial at KiwiPyCon 2014.
Introduction to NLTK, Gensim and TextBlob.
Not enough to make you dangerous but enough to get you interested in natural language processing.