Python Natural Language Processing

Leverage the power of machine learning and deep learning to extract

information from text data About This Book - Implement Machine Learning and

Deep Learning techniques for efficient natural language processing - Get

started with NLTK and implement NLP in your applications with ease -

Understand and interpret human languages with the power of text analysis via

Python Who This Book Is For This book is intended for Python developers who

wish to start with natural language processing and want to make their

applications smarter by implementing NLP in them. What You Will Learn - Focus

on Python programming paradigms, which are used to develop NLP applications -

Understand corpus analysis and different types of data attribute. - Learn NLP

using Python libraries such as NLTK, Polyglot, SpaCy, Standford CoreNLP and so

on - Learn about Features Extraction and Feature selection as part of Features

Engineering. - Explore the advantages of vectorization in Deep Learning. - Get

a better understanding of the architecture of a rule-based system. - Optimize

and fine-tune Supervised and Unsupervised Machine Learning algorithms for NLP

problems. - Identify Deep Learning techniques for Natural Language Processing

and Natural Language Generation problems. In Detail This book starts off by

laying the foundation for Natural Language Processing and why Python is one of

the best options to build an NLP-based expert system with advantages such as

Community support, availability of frameworks and so on. Later it gives you a

better understanding of available free forms of corpus and different types of

dataset. After this, you will know how to choose a dataset for natural

language processing applications and find the right NLP techniques to process

sentences in datasets and understand their structure. You will also learn how

to tokenize different parts of sentences and ways to analyze them. During the

course of the book, you will explore the semantic as well as syntactic

analysis of text. You will understand how to solve various ambiguities in

processing human language and will come across various scenarios while

performing text analysis. You will learn the very basics of getting the

environment ready for natural language processing, move on to the initial

setup, and then quickly understand sentences and language parts. You will

learn the power of Machine Learning and Deep Learning to extract information

from text data. By the end of the book, you will have a clear understanding of

natural language processing and will have worked on multiple examples that

implement NLP in the real world. Style and approach This book teaches the

readers various aspects of natural language Processing using NLTK. It takes

the reader from the basic to advance level in a smooth way.