Book Image

Natural Language Processing with TensorFlow - Second Edition

By : Thushan Ganegedara
2 (1)
Book Image

Natural Language Processing with TensorFlow - Second Edition

2 (1)
By: Thushan Ganegedara

Overview of this book

Learning how to solve natural language processing (NLP) problems is an important skill to master due to the explosive growth of data combined with the demand for machine learning solutions in production. Natural Language Processing with TensorFlow, Second Edition, will teach you how to solve common real-world NLP problems with a variety of deep learning model architectures. The book starts by getting readers familiar with NLP and the basics of TensorFlow. Then, it gradually teaches you different facets of TensorFlow 2.x. In the following chapters, you then learn how to generate powerful word vectors, classify text, generate new text, and generate image captions, among other exciting use-cases of real-world NLP. TensorFlow has evolved to be an ecosystem that supports a machine learning workflow through ingesting and transforming data, building models, monitoring, and productionization. We will then read text directly from files and perform the required transformations through a TensorFlow data pipeline. We will also see how to use a versatile visualization tool known as TensorBoard to visualize our models. By the end of this NLP book, you will be comfortable with using TensorFlow to build deep learning models with many different architectures, and efficiently ingest data using TensorFlow Additionally, you’ll be able to confidently use TensorFlow throughout your machine learning workflow.
Table of Contents (15 chapters)
12
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13
Index

An intuitive understanding of Word2vec – an approach to learning word representation

“You shall know a word by the company it keeps.”

– J.R. Firth

This statement, uttered by J. R. Firth in 1957, lies at the very foundation of Word2vec, as Word2vec techniques use the context of a given word to learn its semantics.

Word2vec is a groundbreaking approach that allows computers to learn the meaning of words without any human intervention. Also, Word2vec learns numerical representations of words by looking at the words surrounding a given word.

We can test the correctness of the preceding quote by imagining a real-world scenario. Imagine you are sitting an exam and you find this sentence in your first question: “Mary is a very stubborn child. Her pervicacious nature always gets her in trouble.” Now, unless you are very clever, you might not know what pervicacious means. In such a situation, you automatically will be...