Neural Networks in Healthcare: Potential and Challenges, Begg Rezaul, Kamruzzaman Joarder, Sarker Ruhul
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: Bishop, Christopher M. Название: Neural Networks for Pattern Recognition ISBN: 0198538642 ISBN-13(EAN): 9780198538646 Издательство: Oxford Academ Рейтинг: Цена: 13939.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is the first to provide a comprehensive account of neural networks from a statistical perspective. Its emphasis is on pattern recognition, which currently represents the area of greatest applicability for neural networks. By focusing on pattern recognition, the book provides a much more extensive treatment of many topics than is available in earlier books.
Автор: Alanis, Alma Название: Artificial Neural Networks for Engineering Applications ISBN: 0128182474 ISBN-13(EAN): 9780128182475 Издательство: Elsevier Science Рейтинг: Цена: 17180.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Hoe bestuur je een wendbare organisatie, of beter, hoe bestuur je een organisatie naar een blijvende wendbare organisatie?¢ Ben jij lid van het Managementteam (MT) of lid van de directie die de noodzaak tot verandering in besturing ziet, die de urgentie voelt om daar iets aan te doen en gehoor hiervoor wil vinden bij de collega leden van het MT of directie? ¢ Ben jij een coach in een organisatie die beweging richting een wendbare organisatie vooral bottom up ziet groeien, een beweging waar je de top down beweging aan toe wil voegen?. In deze pocketguide vind je een praktische methode hoe dit aan te pakken. Besturen in een steeds sneller veranderende wereld. Met de waan van de dag die vaak veel aandacht vraagt en die je kan afleiden van de te behalen resultaten. De auteurs gaan in op het operationaliseren van de strategische organisatiedoelen en daarmee het besturen van de gehele organisatie. De stellingname van dit boek is: maak scherp wat dit kwartaal bereikt moet worden om de strategische doelen te bereiken. Stuur kort cyclisch om te kunnen reageren op veranderende klantwensen of gewijzigde wet- en regelgeving. Werk samen als managementteam of directie richting dje strategische doelen en voorkom dat iedereen in de organisatie vooral een eigen doel nastreeft. Breng meer focus in de operationalisering van de strategie, minder met "brandjes" bezig zijn en meer met het voorkomen ervan. Krijg snel helder wat je medewerkers belemmert in hun werk. Lukt het om de belemmeringen in jouw organisatie snel op te lossen? De kern van deze pocketguide betreft het FOCUS- bord. Deze manier van visual management is een krachtig middel in de besturing. De toepassing ervan zorgt voor samenwerking tussen alle lagen in de organisatie, kort cyclisch sturen en focus op het behalen van de strategische doelen.
Автор: Zhang Название: Toward Deep Neural Networks ISBN: 1138387037 ISBN-13(EAN): 9781138387034 Издательство: Taylor&Francis Рейтинг: Цена: 19140.00 р. Наличие на складе: Поставка под заказ.
Описание: This book introduces deep neural networks, with a focus on the weights-and-structure determination (WASD) algorithm. Based on the authors` 20 years of research experience on neuronets, the book explores the models, algorithms, and applications of the WASD neuronet.
Автор: Rios, Jorge D. Название: Neural Networks Modeling And Control ISBN: 0128170786 ISBN-13(EAN): 9780128170786 Издательство: Elsevier Science Рейтинг: Цена: 19875.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on two methodologies: sliding mode control and Inverse Optimal Neural Control.
As well as considering the different neural control models and complications that are associated with them, this book also analyzes potential applications, prototypes and future trends.
Автор: by Shashi Narayan, Claire Gardent Название: Deep Learning Approaches to Text Production ISBN: 1681737604 ISBN-13(EAN): 9781681737607 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 14276.00 р. Наличие на складе: Нет в наличии.
Описание: Text production has many applications. It is used, for instance, to generate dialogue turns from dialogue moves, verbalise the content of knowledge bases, or generate English sentences from rich linguistic representations, such as dependency trees or abstract meaning representations. Text production is also at work in text-to-text transformations such as sentence compression, sentence fusion, paraphrasing, sentence (or text) simplification, and text summarisation. This book offers an overview of the fundamentals of neural models for text production. In particular, we elaborate on three main aspects of neural approaches to text production: how sequential decoders learn to generate adequate text, how encoders learn to produce better input representations, and how neural generators account for task-specific objectives. Indeed, each text-production task raises a slightly different challenge (e.g, how to take the dialogue context into account when producing a dialogue turn, how to detect and merge relevant information when summarising a text, or how to produce a well-formed text that correctly captures the information contained in some input data in the case of data-to-text generation). We outline the constraints specific to some of these tasks and examine how existing neural models account for them. More generally, this book considers text-to-text, meaning-to-text, and data-to-text transformations. It aims to provide the audience with a basic knowledge of neural approaches to text production and a roadmap to get them started with the related work. The book is mainly targeted at researchers, graduate students, and industrials interested in text production from different forms of inputs.
Автор: Venkateswaran Balaji, Ciaburro Giuseppe Название: Neural Networks with R ISBN: 1788397878 ISBN-13(EAN): 9781788397872 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine learning explores the study and construction of algorithms that can learn from, and make predictions on, data. This book will act as an entry point for anyone who wants to make a career in the field of Machine Learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-M..
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