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Hands-On Python Natural Language Processing

You're reading from   Hands-On Python Natural Language Processing Explore tools and techniques to analyze and process text with a view to building real-world NLP applications

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781838989590
Length 316 pages
Edition 1st Edition
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Authors (2):
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Mayank Rasu Mayank Rasu
Author Profile Icon Mayank Rasu
Mayank Rasu
Aman Kedia Aman Kedia
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Aman Kedia
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Introduction
2. Understanding the Basics of NLP FREE CHAPTER 3. NLP Using Python 4. Section 2: Natural Language Representation and Mathematics
5. Building Your NLP Vocabulary 6. Transforming Text into Data Structures 7. Word Embeddings and Distance Measurements for Text 8. Exploring Sentence-, Document-, and Character-Level Embeddings 9. Section 3: NLP and Learning
10. Identifying Patterns in Text Using Machine Learning 11. From Human Neurons to Artificial Neurons for Understanding Text 12. Applying Convolutions to Text 13. Capturing Temporal Relationships in Text 14. State of the Art in NLP 15. Other Books You May Enjoy
From Human Neurons to Artificial Neurons for Understanding Text

There has been an unprecedented rise in the use of neural network-based applications and architectures in the first two decades of the twenty-first century. This has been largely catered to by the extensive research that has been carried out over the past few decades. The evolution of high-end processors in the form of graphical processing units (GPUs) and tensor processing units (TPUs) has supplemented the rise of neural network-based applications by making it possible to perform heavy calculations that are very commonly encountered in any neural network. Self-driving cars, language translation services, chatbots, document summarization, and image captioning are some common modern-day use cases that are powered by neural networks.

In this chapter, we will begin by looking at how the idea of an artificial neural network...

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