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)

Natural language understanding

Let's learn about natural language understanding:

  • Natural language understanding (NLU) is considered the first component of NLP
  • NLU is considered an Artificial Intelligence-Hard (AI-Hard) problem or Artificial Intelligence-Complete (AI-Complete) problem
  • NLU is considered an AI-Hard problem because we are trying to make a computer as intelligent as a human
  • NLU is hard, but nowadays, tech giants and research communities are improvising traditional Machine Learning algorithms and applying various types of deep neural network that will help to achieve the goal (computers can also have the intelligence to process natural language (NL))
  • NLU is defined as the process of converting NL input into useful a representation by using computational linguistics tools
  • NLU requires the following analysis to convert NL into a useful representation:
    • Morphological...