NLTK Essentials

Nonfiction, Computers, Advanced Computing, Natural Language Processing, Programming, Programming Languages
Cover of the book NLTK Essentials by Nitin Hardeniya, Packt Publishing
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Author: Nitin Hardeniya ISBN: 9781784398507
Publisher: Packt Publishing Publication: July 27, 2015
Imprint: Packt Publishing Language: English
Author: Nitin Hardeniya
ISBN: 9781784398507
Publisher: Packt Publishing
Publication: July 27, 2015
Imprint: Packt Publishing
Language: English

Natural Language Processing (NLP) is the field of artificial intelligence and computational linguistics that deals with the interactions between computers and human languages. With the instances of human-computer interaction increasing, it’s becoming imperative for computers to comprehend all major natural languages. Natural Language Toolkit (NLTK) is one such powerful and robust tool.

You start with an introduction to get the gist of how to build systems around NLP. We then move on to explore data science-related tasks, following which you will learn how to create a customized tokenizer and parser from scratch. Throughout, we delve into the essential concepts of NLP while gaining practical insights into various open source tools and libraries available in Python for NLP. You will then learn how to analyze social media sites to discover trending topics and perform sentiment analysis. Finally, you will see tools which will help you deal with large scale text.

By the end of this book, you will be confident about NLP and data science concepts and know how to apply them in your day-to-day work.

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Natural Language Processing (NLP) is the field of artificial intelligence and computational linguistics that deals with the interactions between computers and human languages. With the instances of human-computer interaction increasing, it’s becoming imperative for computers to comprehend all major natural languages. Natural Language Toolkit (NLTK) is one such powerful and robust tool.

You start with an introduction to get the gist of how to build systems around NLP. We then move on to explore data science-related tasks, following which you will learn how to create a customized tokenizer and parser from scratch. Throughout, we delve into the essential concepts of NLP while gaining practical insights into various open source tools and libraries available in Python for NLP. You will then learn how to analyze social media sites to discover trending topics and perform sentiment analysis. Finally, you will see tools which will help you deal with large scale text.

By the end of this book, you will be confident about NLP and data science concepts and know how to apply them in your day-to-day work.

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