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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

Let's talk Keras

Keras is a high-level framework that can be used to build neural networks. It is written in Python and provides numerous APIs and modules for defining, building, and training neural networks with ease. It can use multiple platforms, such as TensorFlow, in its backend.

TensorFlow is an open source library developed by Google for machine learning model building and deployment. It provides several low-level controls as well.

Keras provides a wrapper around frameworks such as TensorFlow and hides low-lying implementations that let developers concentrate on solving problems using deep learning by taking care of all internal implementations and interfacing with backend frameworks, such as TensorFlow.

A neural network can be envisioned as a computational graph in which layers are stacked. Keras provides an interface to build these stacks of layers. The simplest among these is the sequential model, which is nothing but a linear stack of layers. It can be imported and instantiated...

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