Natural Language Processing with Python
by Steven Bird, Ewan Klein, Edward Loper
Publisher: O'Reilly Media 2009
Number of pages: 512
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.
Home page url
Download or read it online for free here:
by Richard Gruet
This reference covers invocation options, environment variables, lexical entities, basic types and their operations, advanced types, statements, iterators, generators, descriptors, decorators, built-in functions, built-in exceptions, and more.
by Steven Thurlow - Wikibooks
Contents of Beginner's Python Tutorial: Installing Python; Very Simple Programs; Variables, Scripts; Loops, Conditionals; Functions; Tuples, Lists, Dictionaries; for Loop; Classes; Importing Modules; File I/O; Exception Handling.
by Rahul Verma, Chetan Giridhar - Testing Perspective
This book is about learning design patterns with Python language. If you are new to design patterns, this text provides the first building blocks. If you are interested in design of test automation frameworks, this book will be very useful.
by Nathan Yergler - PyCon
Effective Django development means building applications that are testable, maintainable, and scalable. After reading this book you should have an understanding of how Django's pieces fit together and how to use them to engineer web applications.