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Natural Language Processing and Computational Linguistics

Natural Language Processing and Computational Linguistics

By : Bhargav Srinivasa-Desikan
3.6 (7)
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Natural Language Processing and Computational Linguistics

Natural Language Processing and Computational Linguistics

3.6 (7)
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 (17 chapters)
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What is POS-tagging?

The obvious first step in understanding POS-tagging is to expand the acronym Part-Of-Speech tagging. Now, that makes things a lot easier now, doesn't it? As the name suggests, it is the process of tagging words in a textual input with their appropriate part of speech. We've already discussed this before briefly, particularly when dealing with spaCy and its language models. So, while we know that POS-tagging refers to the action of tagging words with their POS, we haven't talked very much about what exactly a part of speech in natural language (and in particular, English) is, and why it might be relevant to us in the realm of text analysis.

Traditionally, a part of speech is a category of words which have similar grammatical properties or usage. We will be focusing our efforts on the English language (as we have been and will continue...

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