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

by Yoav Goldberg

Book Reviews

  • Neural Network Methods for NLP (Yoav Goldberg) NLP is a very broad field. However, most of the attention in recent years has been on neural networks and how they apply to address NLP tasks and applications. If that is your interest, try this book. https://t.co/uOQXFmrmYh https://t.co/ycuAWqiXRCLink to Tweet

About Book

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.