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Deep learning for natural language p...

Goyal, Palash.

Deep learning for natural language processingcreating neural networks with Python /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning for natural language processingby Palash Goyal, Sumit Pandey, Karan Jain.
Reminder of title:	creating neural networks with Python /
Author:	Goyal, Palash.
other author:	Pandey, Sumit.
Published:	Berkeley, CA :Apress :2018.
Description:	xvii, 277 p. :digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Natural language processing (Computer science)
Online resource:	http://dx.doi.org/10.1007/978-1-4842-3685-7
ISBN:	9781484236857$q(electronic bk.)

Deep learning for natural language processingcreating neural networks with Python /
Goyal, Palash.

Deep learning for natural language processingcreating neural networks with Python /[electronic resource] :by Palash Goyal, Sumit Pandey, Karan Jain. - Berkeley, CA :Apress :2018. - xvii, 277 p. :digital ;24 cm.

Chapter 1: Introduction to NLP and Deep Learning -- Chapter 2: Word Vector representations -- Chapter 3: Unfolding Recurrent Neural Networks -- Chapter 4: Developing a Chatbot -- Chapter 5: Research Paper Implementation: Sentiment Classification.

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. You'll 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. You will: Gain the fundamentals of deep learning and its mathematical prerequisites Discover deep learning frameworks in Python Develop a chatbot Implement a research paper on sentiment classification.

ISBN: 9781484236857$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-3685-7doiSubjects--Topical Terms:

200539
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38 / G693 2018

Dewey Class. No.: 006.35

Deep learning for natural language processingcreating neural networks with Python /
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505 0 $a Chapter 1: Introduction to NLP and Deep Learning -- Chapter 2: Word Vector representations -- Chapter 3: Unfolding Recurrent Neural Networks -- Chapter 4: Developing a Chatbot -- Chapter 5: Research Paper Implementation: Sentiment Classification.
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