Neural Networks for Natural Language Processing, Sumathi S, Janani M
Автор: Aliev Rafik Aziz Название: Arithmetic of Z-Numbers ISBN: 9814675288 ISBN-13(EAN): 9789814675284 Издательство: World Scientific Publishing Рейтинг: Цена: 16632.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Real-world information is imperfect and is usually described in natural language (NL). Moreover, this information is often partially reliable and a degree of reliability is also expressed in NL.
Автор: Sumathi S, Janani M Название: Neural Networks for Natural Language Processing ISBN: 1799811603 ISBN-13(EAN): 9781799811602 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 26334.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Information in today's advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.
Автор: Luo Fa-Long Название: Applied Neural Networks for Signal Processing ISBN: 0521644003 ISBN-13(EAN): 9780521644006 Издательство: Cambridge Academ Рейтинг: Цена: 9979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A comprehensive introduction to the use of neural networks in signal processing, covering basic principles and practical implementation procedures. A key feature of the book is that many carefully designed simulation examples are included to help guide the reader in the development of systems for new applications.
Автор: Gerard Chollet; Maria-Gabriella Di Benedetto; Anna Название: Speech Processing, Recognition and Artificial Neural Networks ISBN: 1852330945 ISBN-13(EAN): 9781852330941 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Speech Processing, Recognition and Artificial Neural Networks contains papers from leading researchers and selected students, discussing the experiments, theories and perspectives of acoustic phonetics as well as the latest techniques in the field of spe ech science and technology. Auditory and Neural Network Models for Speech;
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11504.00 р. Наличие на складе: Нет в наличии.
Описание: 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.
Автор: Lambert Spaanenburg, Suleyman Malki Название: Robust Embedded Intelligence on Cellular Neural Networks ISBN: 8770221006 ISBN-13(EAN): 9788770221009 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 13167.00 р. Наличие на складе: Нет в наличии.
Описание: Machine Intelligence (MI) is the motor that drives the modern information-rich society. Supercomputing and parallel coding have made MI programs feasible and the theoretical base of MI has matured. Graphical Processors (GPs) have found new life as carrier for low-cost supercomputing. The road towards lower cost & size leads to embedding systems, such as self-driving cars and intelligent houses. Machine intelligence has not only opened many disruptive venues but given simultaneously a lot of anxiety. Compared to the many accidents in the early days of automotive traffic, the few problems with the TESLA cars are already sufficient for major concern. Evidently, still research is required to bring MI on the appropriate safety levels that rule the type tests for acceptance on the European automotive market. In the ACM Turing Award 2018, Hennessey and Patterson prophesize the breakthrough of Domain-Specific Processor. A typical example is the modern vision hardware in the automotive domain. Such applications bring collectively self-driving in reach for safety concerns. It features a domain-specific mix of hardware and software. Hardware can be correctly designed & manufactured and will not change afterwards. Software can be formally proven but efficiency requires to keep it close to the platform. Robust Embedded Intelligence on Cellular Neural Networks makes the reader familiar with the mathematical and electronic techniques to turn a data-driven problem into a safe embedded solution. In particular, it treats aspects on Cellular Neural Networks (CNN) for reliable visual recognition in a wide range of practical applications, highlighting vein feature extraction and license plate recognition.
Автор: Johnson I. Agbinya Название: Applied Data Analytics - Principles and Applications ISBN: 8770220964 ISBN-13(EAN): 9788770220965 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The emergence of huge amounts of data which require analysis and in some cases real-time processing has forced exploration into fast algorithms for handling very lage data sizes. Analysis of x-ray images in medical applications, cyber security data, crime data, telecommunications and stock market data, health records and business analytics data are but a few areas of interest. Applications and platforms including R, RapidMiner and Weka provide the basis for analysis, often used by practitioners who pay little to no attention to the underlying mathematics and processes impacting the data. This often leads to an inability to explain results or correct mistakes, or to spot errors.
Applied Data Analytics - Principles and Applications seeks to bridge this missing gap by providing some of the most sought after techniques in big data analytics. Establishing strong foundations in these topics provides practical ease when big data analyses are undertaken using the widely available open source and commercially orientated computation platforms, languages and visualisation systems. The book, when combined with such platforms, provides a complete set of tools required to handle big data and can lead to fast implementations and applications.
The book contains a mixture of machine learning foundations, deep learning, artificial intelligence, statistics and evolutionary learning mathematics written from the usage point of view with rich explanations on what the concepts mean. The author has thus avoided the complexities often associated with these concepts when found in research papers. The tutorial nature of the book and the applications provided are some of the reasons why the book is suitable for undergraduate, postgraduate and big data analytics enthusiasts.
This text should ease the fear of mathematics often associated with practical data analytics and support rapid applications in artificial intelligence, environmental sensor data modelling and analysis, health informatics, business data analytics, data from Internet of Things and deep learning applications.
Автор: Aboul Ella Hassanien, Ashraf Darwish, Chiranji Lal Chowdhary Название: Handbook of Research on Deep Learning Innovations and Trends ISBN: 1522578625 ISBN-13(EAN): 9781522578628 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 43105.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Leading technology firms and research institutions are continuously exploring new techniques in artificial intelligence and machine learning. As such, deep learning has now been recognized in various real-world applications such as computer vision, image processing, biometrics, pattern recognition, and medical imaging. The deep learning approach has opened new opportunities that can make such real-life applications and tasks easier and more efficient. The Handbook of Research on Deep Learning Innovations and Trends is an essential scholarly resource that presents current trends and the latest research on deep learning and explores the concepts, algorithms, and techniques of data mining and analysis. Highlighting topics such as computer vision, encryption systems, and biometrics, this book is ideal for researchers, practitioners, industry professionals, students, and academicians.
Описание: Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This modern treatment of real world cases offers neuroscience researchers and graduate students a comprehensive, in-depth guide to statistical and machine learning methods.
Автор: Philipp Koehn Название: Neural Machine Translation ISBN: 1108497322 ISBN-13(EAN): 9781108497329 Издательство: Cambridge Academ Рейтинг: Цена: 9979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Deep learning is revolutionizing how machine translation systems are built today. This introduction to machine translation starts from the basics of neural network methods and reaches the state of the art, while giving illuminating historical, linguistic, and applied context. Code examples in Python give a hands-on blueprint for implementation.
Описание: While cognitive informatics and natural intelligence are receiving greater attention by researchers, multidisciplinary approaches still struggle with fundamental problems involving psychology and neurobiological processes of the brain. Examining the difficulties of certain approaches using the tools already available is vital for propelling knowledge forward and making further strides.
Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence is a collection of innovative research that examines the enhancement of human cognitive performance using emerging technologies. Featuring research on topics such as parallel computing, neuroscience, and signal processing, this book is ideally designed for engineers, computer scientists, programmers, academicians, researchers, and students.
Описание: While cognitive informatics and natural intelligence are receiving greater attention by researchers, multidisciplinary approaches still struggle with fundamental problems involving psychology and neurobiological processes of the brain. Examining the difficulties of certain approaches using the tools already available is vital for propelling knowledge forward and making further strides.
Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence is a collection of innovative research that examines the enhancement of human cognitive performance using emerging technologies. Featuring research on topics such as parallel computing, neuroscience, and signal processing, this book is ideally designed for engineers, computer scientists, programmers, academicians, researchers, and students.
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