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Deep Learning for Natural Language Processing
Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing: Solve your natural language processing problems with smart deep neural networks

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Profile Icon Karthiek Reddy Bokka Profile Icon Shubhangi Hora Profile Icon Tanuj Jain Profile Icon Monicah Wambugu
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$9.99 $26.99
Full star icon Half star icon Empty star icon Empty star icon Empty star icon 1.5 (2 Ratings)
eBook Jun 2019 372 pages 1st Edition
eBook
$9.99 $26.99
Paperback
$38.99
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Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Karthiek Reddy Bokka Profile Icon Shubhangi Hora Profile Icon Tanuj Jain Profile Icon Monicah Wambugu
Arrow right icon
$9.99 $26.99
Full star icon Half star icon Empty star icon Empty star icon Empty star icon 1.5 (2 Ratings)
eBook Jun 2019 372 pages 1st Edition
eBook
$9.99 $26.99
Paperback
$38.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
$9.99 $26.99
Paperback
$38.99
Subscription
Free Trial
Renews at $19.99p/m

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Deep Learning for Natural Language Processing

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Key benefits

  • Gain insights into the basic building blocks of natural language processing
  • Learn how to select the best deep neural network to solve your NLP problems
  • Explore convolutional and recurrent neural networks and long short-term memory networks

Description

Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts by highlighting the basic building blocks of the natural language processing domain. The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you’ll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search. By the end of this book, you will not only have sound knowledge of natural language processing, but also be able to select the best text preprocessing and neural network models to solve a number of NLP issues.

Who is this book for?

If you’re an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you. Strong working knowledge of Python, linear algebra, and machine learning is a must.

What you will learn

  • Understand various preprocessing techniques for solving deep learning problems
  • Build a vector representation of text using word2vec and GloVe
  • Create a named entity recognizer and parts-of-speech tagger with Apache OpenNLP
  • Build a machine translation model in Keras
  • Develop a text generation application using LSTM
  • Build a trigger word detection application using an attention model

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 11, 2019
Length: 372 pages
Edition : 1st
Language : English
ISBN-13 : 9781838553678
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What do you get with eBook?

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Product Details

Publication date : Jun 11, 2019
Length: 372 pages
Edition : 1st
Language : English
ISBN-13 : 9781838553678
Category :
Languages :

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Frequently bought together


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Total $ 126.97
Deep Learning for Natural Language Processing
$38.99
Hands-On Natural Language Processing with Python
$43.99
Natural Language Processing Fundamentals
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Total $ 126.97 Stars icon
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Table of Contents

9 Chapters
Introduction to Natural Language Processing Chevron down icon Chevron up icon
Applications of Natural Language Processing Chevron down icon Chevron up icon
Introduction to Neural Networks Chevron down icon Chevron up icon
Foundations of Convolutional Neural Network Chevron down icon Chevron up icon
Recurrent Neural Networks Chevron down icon Chevron up icon
Gated Recurrent Units (GRUs) Chevron down icon Chevron up icon
Long Short-Term Memory (LSTM) Chevron down icon Chevron up icon
State-of-the-Art Natural Language Processing Chevron down icon Chevron up icon
A Practical NLP Project Workflow in an Organization Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Half star icon Empty star icon Empty star icon Empty star icon 1.5
(2 Ratings)
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3 star 0%
2 star 50%
1 star 50%
Claus Jul 30, 2020
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
Ich behalte mir noch vor, dass Buch direkt an den Verlag zurückzuschicken, da das Druckbild der Code-Zeilen komplett unleserlich ist.Ist ja toll, dass man von Packt die Bücher jetzt (wahrscheinlich) also print on demand bekommt - nur leidet die Druckqualität so stark, so dass man bei vielen Codezeilen rätseln muss: "Was wollte der Autor mir damit sagen ... welche Buchstaben stellt diese Kritzelei dar?"
Amazon Verified review Amazon
Jen Nov 05, 2019
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Lots of weird printing issues that make parts of the text unreadable.
Amazon Verified review Amazon
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