Book Image

Python Natural Language Processing

Book Image

Python Natural Language Processing

Overview of this book

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.
Table of Contents (13 chapters)

Semantic analysis

Semantic analysis is basically focused on the meaning of the NL. Its definition, various elements of it, and its application are explored in this section.

Now let's begin our semantic journey, which is quite interesting if you want to do some cool research in this branch.

What is semantic analysis?

Semantic analysis is generating representation for meaning of the NL. You might think, if lexical analysis also focuses on the meaning of the words given in stream of text, then what is the difference between semantic analysis and lexical analysis? The answer is that lexical analysis is based on smaller tokens; its focus is on meaning of the words, but semantic analysis focuses on larger chunks. Semantic analysis...