Deep Learning for Natural Language Processing (Paperback)

Language: English

Published by APress, Berkley, 2018

148423684X / 9781484236840

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Paperback. Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models.Youll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with practical examples. The first three chapters of the book cover the basics of NLP, starting with word-vector representation before moving onto advanced algorithms. The final chapters focus entirely on implementation, and deal with sophisticated architectures such as RNN, LSTM, and Seq2seq, using Python tools: TensorFlow, and Keras. Deep Learning for Natural Language Processing follows a progressive approach and combines all the knowledge you have gained to build a question-answer chatbot system.This book is a good starting point for people who want to get started in deep learning for NLP. All the code presented in the book will be available in the form of IPython notebooks and scripts, which allow you to try out the examples and extend them in interesting ways.What You Will LearnGain the fundamentals of deep learning and its mathematical prerequisitesDiscover deep learning frameworks in Python Develop a chatbot Implement a research paper on sentiment classificationWho This Book Is ForSoftware developers who are curious to try out deep learning with NLP. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Seller Inventory # 9781484236840

Title
Deep Learning for Natural Language Processing (Paperback)
Author
Palash Goyal
Publisher
APress, Berkley
Publication year
2018
Condition
new
Binding
Paperback
Language
English
ISBN 10
148423684X
ISBN 13
9781484236840
Edition
1st Edition

AussieBookSeller

Truganina, VIC, Australia

5-star seller

AbeBooks seller since June 22, 2007

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