Connectionists: Morgan & Claypool New Title: Neural Network Methods for Natural Language Processing

[Bebe Barrow]

Dear Connectionists Listserv Member,

 

I am pleased to announce a new title in Morgan & Claypool's series on Human
Language Technologies:

 

Neural Network Methods for Natural Language Processing

Yoav Goldberg, Bar Ilan University

Paperback ISBN: 9781627052986, $74.95

eBook ISBN: 9781627052955

April 2017, 309 pages

http://dx.doi.org/10.2200/S00762ED1V01Y201703HLT037 

 

Abstract:

Neural networks are a family of powerful machine learning models. This book
focuses on the application of neural network models to natural language
data. The first half of the book (Parts I and II) covers the basics of
supervised machine learning and feed-forward neural networks, the basics of
working with machine learning over language data, and the use of
vector-based rather than symbolic representations for words. It also covers
the computation-graph abstraction, which allows to easily define and train
arbitrary neural networks, and is the basis behind the design of
contemporary neural network software libraries.

 

The second part of the book (Parts III and IV) introduces more specialized
neural network architectures, including 1D convolutional neural networks,
recurrent neural networks, conditioned-generation models, and
attention-based models. These architectures and techniques are the driving
force behind state-of-the-art algorithms for machine translation, syntactic
parsing, and many other applications. Finally, we also discuss tree shaped
networks, structured prediction, and the prospects of multi-task learning.

 

Table of Contents: Preface / Acknowledgments / Introduction / Learning
Basics and Linear Models / From Linear Models to Multi-layer Perceptrons /
Feed-forward Neural Networks / Neural Network Training / Features for
Textual Data / Case Studies of NLP Features / From Textual Features to
Inputs / Language Modeling / Pre-trained Word Representations / Using Word
Embeddings / Case Study: A Feed-forward Architecture for Sentence Meaning
Inference / Ngram Detectors: Convolutional Neural Networks / Recurrent
Neural Networks: Modeling Sequences and Stacks / Concrete Recurrent Neural
Network Architectures / Modeling with Recurrent Networks / Conditioned
Generation / Modeling Trees with Recursive Neural Networks / Structured
Output Prediction / Cascaded, Multi-task and Semi-supervised Learning /
Conclusion / Bibliography / Author's Biography

Visit this title's abstract page on our website:

http://www.morganclaypool.com/doi/abs/10.2200/S00762ED1V01Y201703HLT037 

 

 

Morgan & Claypool Bookstore Link:

http://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?produc
ts_id=1056

 

Series: Synthesis Lectures on Human Language Technologies

Editor: Graeme Hirst, University of Toronto

http://www.morganclaypool.com/toc/hlt/10/1

 

 

Please e-mail me if you have any questions.

 

Thank you,

Bebe Barrow

 

 

--

Bebe Barrow

Sales & Marketing Assistant

Morgan & Claypool Publishers

barrow at morganclaypool.com <mailto:carreon at morganclaypool.com> 

 

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