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Neural Network Methods in Natural Language Processing (Synthesis Lectures on Human Language Technologies)

Amazon.com Price:  $71.20 (as of 22/04/2019 22:31 PST- Details)

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Description

Neural networks are a circle of relatives of powerful machine learning models. This book makes a speciality of 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 usage of vector-based quite 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 at the back of the design of up to date neural network software libraries.

The second a 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 motive force at the back of state of the art algorithms for machine translation, syntactic parsing, and many other applications. After all, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

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