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Author: J. Leo van Hemmen
Publisher: Springer Science & Business Media
ISBN: 0387217037
Category : Computers
Languages : en
Pages : 424
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Book Description
This volume, with chapters by leading researchers in the field, is devoted to early vision and attention, that is, to the first stages of visual information processing. This state-of-the-art look at biological neural networks spans the many subfields, such as computational and experimental neuroscience; anatomy and physiology; visual information processing and scene segmentation; perception at illusory contours; control of visual attention; and paradigms for computing with spiking neurons.
Author: J. Leo van Hemmen
Publisher: Springer Science & Business Media
ISBN: 0387217037
Category : Computers
Languages : en
Pages : 424
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Book Description
This volume, with chapters by leading researchers in the field, is devoted to early vision and attention, that is, to the first stages of visual information processing. This state-of-the-art look at biological neural networks spans the many subfields, such as computational and experimental neuroscience; anatomy and physiology; visual information processing and scene segmentation; perception at illusory contours; control of visual attention; and paradigms for computing with spiking neurons.
Author: Leo van Hemmen
Publisher:
ISBN: 9786610187386
Category :
Languages : en
Pages :
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Book Description
Author: Rob J Hyndman
Publisher: OTexts
ISBN: 0987507117
Category : Business & Economics
Languages : en
Pages : 380
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Book Description
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Author: Emil Hvitfeldt
Publisher: CRC Press
ISBN: 1000461971
Category : Computers
Languages : en
Pages : 402
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Book Description
Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.
Author: Randolph W. Parks
Publisher: MIT Press
ISBN: 9780262161756
Category : Cognition
Languages : en
Pages : 450
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Book Description
Provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. Over the past few years, computer modeling has become more prevalent in the clinical sciences as an alternative to traditional symbol-processing models. This book provides an introduction to the neural network modeling of complex cognitive and neuropsychological processes. It is intended to make the neural network approach accessible to practicing neuropsychologists, psychologists, neurologists, and psychiatrists. It will also be a useful resource for computer scientists, mathematicians, and interdisciplinary cognitive neuroscientists. The editors (in their introduction) and contributors explain the basic concepts behind modeling and avoid the use of high-level mathematics. The book is divided into four parts. Part I provides an extensive but basic overview of neural network modeling, including its history, present, and future trends. It also includes chapters on attention, memory, and primate studies. Part II discusses neural network models of behavioral states such as alcohol dependence, learned helplessness, depression, and waking and sleeping. Part III presents neural network models of neuropsychological tests such as the Wisconsin Card Sorting Task, the Tower of Hanoi, and the Stroop Test. Finally, part IV describes the application of neural network models to dementia: models of acetycholine and memory, verbal fluency, Parkinsons disease, and Alzheimer's disease. Contributors J. Wesson Ashford, Rajendra D. Badgaiyan, Jean P. Banquet, Yves Burnod, Nelson Butters, John Cardoso, Agnes S. Chan, Jean-Pierre Changeux, Kerry L. Coburn, Jonathan D. Cohen, Laurent Cohen, Jose L. Contreras-Vidal, Antonio R. Damasio, Hanna Damasio, Stanislas Dehaene, Martha J. Farah, Joaquin M. Fuster, Philippe Gaussier, Angelika Gissler, Dylan G. Harwood, Michael E. Hasselmo, J, Allan Hobson, Sam Leven, Daniel S. Levine, Debra L. Long, Roderick K. Mahurin, Raymond L. Ownby, Randolph W. Parks, Michael I. Posner, David P. Salmon, David Servan-Schreiber, Chantal E. Stern, Jeffrey P. Sutton, Lynette J. Tippett, Daniel Tranel, Bradley Wyble
Author: Yoav Goldberg
Publisher: Springer Nature
ISBN: 3031021657
Category : Computers
Languages : en
Pages : 20
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Book Description
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.
Author: Martin T. Hagan
Publisher:
ISBN: 9789812403766
Category : Neural networks (Computer science)
Languages : en
Pages :
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Book Description
Author: Berndt Müller
Publisher: Springer Science & Business Media
ISBN: 3642577601
Category : Computers
Languages : en
Pages : 340
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Book Description
Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.
Author: Stephen I. Gallant
Publisher: MIT Press
ISBN: 9780262071451
Category : Computers
Languages : en
Pages : 392
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Book Description
presents a unified and in-depth development of neural network learning algorithms and neural network expert systems
Author: Pierre Peretto
Publisher: Cambridge University Press
ISBN: 9780521424875
Category : Computers
Languages : en
Pages : 496
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Book Description
This book is a beginning graduate-level introduction to neural networks which is divided into four parts.
