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Explore deep neural network architectures and their application areas to overcome your NLP issuesKey FeaturesGet to grips with the basic building blocks of natural language processingUnderstand how to select the most suitable deep neural network to solve your NLP problemsExplore convolutional and recurrent neural networks and long short-term memory networksBook DescriptionApplying deep learning approaches to various NLP tasks can take your computational algorithms to an entirely new level in terms of speed and accuracy.Starting with the building blocks of natural language processing, this deep learning book will introduce you to the problems that you can solve using state-of-the-art neural network models. After this, you'll delve into the various neural network architectures and their areas of application to understand how to select the model best suited to your needs. As you make progress, you'll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory (LSTM) neural networks. Understanding these networks will help you to implement their models using Keras. In later chapters, you will learn how to develop a trigger word detection application using NLP techniques such as the attention model and beam search.By the end of this book, you will not only have developed a sound knowledge of natural language processing but also be able to select text preprocessing and neural network models that are best suited to solve different NLP issues.What you will learnUnderstand various preprocessing techniques for solving deep learning problemsUse word2vec and GloVe to build a vector representation of textCreate a named entity recognizer and parts-of-speech tagger with Apache OpenNLPBuild a machine translation model in KerasDevelop a text generation application using LSTMBuild a trigger word detection application using the attention modelWho this book is forIf you're a data science enthusiast looking for an introduction to deep learning in the NLP domain, this is just the book for you. Strong working knowledge of Python, linear algebra, and machine learning required.Table of ContentsIntroduction to Natural Language ProcessingApplication of Natural Language ProcessingIntroduction to Neural NetworksFoundations of Convolutional Neural NetworkRecurrent Neural NetworksGated Recurrent UnitsLong Short-Term Memory (LSTM)State-of-the-Art Natural Language ProcessingA Practical NLP Project Workflow in an Organization
eBook details
- Title: Deep Learning for Natural Language Processing: Solve your natural language processing problems with smart deep neural networks
- Author : Karthiek Reddy Bokka, Shubhangi Hora, Tanuj Jain, Monicah Wambugu
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- Genre: Kindle Store,Kindle eBooks,Computers & Technology
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