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)

Understanding the basics of word2vec

Here, we will try to handle semantics at word level by using word2vec. Then, we will expand our concepts to paragraph level and document level. By looking at Figure 6.1, you will see the different kinds of semantics that we are going to cover in this book:

Figure 6.1: Different kinds of semantics

Semantics is a branch that deals with meaning in the area of NLP. We have already covered lexical semantic in Chapter 3, Understanding Structure of Sentences. So, here we will discuss more about distributional semantics. There are also other techniques or types in semantics, such as formal semantics compositional semantics; but right now, in this book, we are not going to cover these types or techniques.

Distributional semantics

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