Book Image

Natural Language Processing and Computational Linguistics

By : Bhargav Srinivasa-Desikan
Book Image

Natural Language Processing and Computational Linguistics

By: Bhargav Srinivasa-Desikan

Overview of this book

Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis.
Table of Contents (22 chapters)
Title Page
Copyright and Credits
Packt Upsell

Chapter 1. What is Text Analysis?

There is no time like now to do text analysis – we have an abundance of easily available data, powerful and free open source tools to conduct our analysis, and research on machine learning, computational linguistics and computing with text is progressing at a pace we have not seen before.

In this chapter, we will go into details about what exactly text analysis is and look at the motivations for studying and understanding text analysis. Following are the topics we will cover in this chapter:

  • What is text analysis?
  • Where's the data at?
  • Garbage in, garbage out
  • Why should YOU be interested?
  • References

A note about the references: they will appear throughout the PDF version of the book as links, and if it is an academic reference it will link to the PDF of the reference or the journal page. All of these links and references are then displayed as the final section of the chapter, so offline readers can also visit the websites or research papers.