Natural Language Processing with Python Cookbook

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Synopsis

Learn the tricks and tips that will help you design Text Analytics solutions

Key Features

Independent recipes that will teach you how to efficiently perform Natural Language Processing in Python

Use dictionaries to create your own named entities using this easy-to-follow guide

Learn how to implement NLTK for various scenarios with the help of example-rich recipes to take you beyond basic Natural Language Processing

Book Description

Natural Language Processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages; in particular, it's about programming computers to fruitfully process large natural language corpora.

This book includes unique recipes that will teach you various aspects of performing Natural Language Processing with NLTK the leading Python platform for the task. You will come across various recipes during the course, covering (among other topics) natural language understanding, Natural Language Processing, and syntactic analysis. You will learn how to understand language, plan sentences, and work around various ambiguities. You will learn how to efficiently use NLTK and implement text classification, identify parts of speech, tag words, and more. You will also learn how to analyze sentence structures and master lexical analysis, syntactic and semantic analysis, pragmatic analysis, and the application of deep learning techniques.

By the end of this book, you will have all the knowledge you need to implement Natural Language Processing with Python.

What You Will Learn

Explore corpus management using internal and external corpora

Learn WordNet usage and a couple of simple application assignments using WordNet

Operate on raw text

Learn to perform tokenization, stemming, lemmatization, and spelling corrections, stop words removals, and more

Understand regular expressions for pattern matching

Learn to use and write your own POS taggers and grammars

Learn to evaluate your own trained models

Explore Deep Learning techniques in NLP

Generate Text from Nietzsche's writing using LSTM

Utilize the BABI dataset and LSTM to model episodes

Copyright:
2017

Book Details

Book Quality:
Publisher Quality
ISBN-13:
9781787289321
Publisher:
Packt
Date of Addition:
Copyrighted By:
Packt
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.

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