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Añadir al carritoPaperback or Softback. Condición: New. Artificial Neural Networks with Java: Tools for Building Neural Network Applications. Book.
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Añadir al carritoPaperback. Condición: new. Paperback. Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks. This book discusses the practical aspects of using Java for neural network processing. You will know how to use the Encog Java framework for processing large-scale neural network applications. Also covered is the use of neural networks for approximation of non-continuous functions. In addition to using neural networks for regression, this second edition shows you how to use neural networks for computer vision.It focuses on image recognition such as the classification of handwritten digits, input data preparation and conversion, and building the conversion program. And you will learn about topics related to the classification of handwritten digits such as network architecture, program code, programming logic, and execution. The step-by-step approach taken in the book includes plenty of examples, diagrams, and screenshots to help you grasp the concepts quickly and easily.What You Will LearnUse Java for the development of neural network applicationsPrepare data for many different tasksCarry out some unusual neural network processingUse a neural network to process non-continuous functionsDevelop a program that recognizes handwritten digitsWho This Book Is ForIntermediate machine learning and deep learning developers who are interested in switching to Java Intermediate-Advanced user level Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoPaperback. Condición: new. Paperback. Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks. This book discusses the practical aspects of using Java for neural network processing. You will know how to use the Encog Java framework for processing large-scale neural network applications. Also covered is the use of neural networks for approximation of non-continuous functions. In addition to using neural networks for regression, this second edition shows you how to use neural networks for computer vision.It focuses on image recognition such as the classification of handwritten digits, input data preparation and conversion, and building the conversion program. And you will learn about topics related to the classification of handwritten digits such as network architecture, program code, programming logic, and execution. The step-by-step approach taken in the book includes plenty of examples, diagrams, and screenshots to help you grasp the concepts quickly and easily.What You Will LearnUse Java for the development of neural network applicationsPrepare data for many different tasksCarry out some unusual neural network processingUse a neural network to process non-continuous functionsDevelop a program that recognizes handwritten digitsWho This Book Is ForIntermediate machine learning and deep learning developers who are interested in switching to Java Intermediate-Advanced user level Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Añadir al carritoTaschenbuch. Condición: Neu. Artificial Neural Networks with Java | Tools for Building Neural Network Applications | Igor Livshin | Taschenbuch | xviii | Englisch | 2021 | Apress | EAN 9781484273678 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks.This book discusses the practical aspects of using Java for neural network processing. You will know how to use the Encog Java framework for processing large-scale neural network applications. Also covered is the use of neural networks for approximation of non-continuous functions.In addition to using neural networks for regression, this second edition shows you how to use neural networks for computer vision.It focuses on image recognition such as the classification of handwritten digits, input data preparation and conversion, and building the conversion program. And you will learn about topics related to the classification of handwritten digits such as network architecture, program code, programming logic, and execution.The step-by-step approach taken in the book includes plenty of examples, diagrams, and screenshots to help you grasp the concepts quickly and easily.What You Will LearnUse Java for the development of neural network applicationsPrepare data for many different tasksCarry out some unusual neural network processingUse a neural network to process non-continuous functionsDevelop a program that recognizes handwritten digitsWho This Book Is ForIntermediate machine learning and deep learning developers who are interested in switching to Java 631 pp. Englisch.
Publicado por Springer, Berlin|Apress, 2022
ISBN 10: 1484273672 ISBN 13: 9781484273678
Idioma: Inglés
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Intermediate-Advanced user levelDevelop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. .
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks.This book discusses the practical aspects of using Java for neural network processing. You will know how to use the Encog Java framework for processing large-scale neural network applications. Also covered is the use of neural networks for approximation of non-continuous functions.In addition to using neural networks for regression, this second edition shows you how to use neural networks for computer vision.It focuses on image recognition such as the classification of handwritten digits, input data preparation and conversion, and building the conversion program. And you will learn about topics related to the classification of handwritten digits such as network architecture, program code, programming logic, and execution.The step-by-step approach taken in the book includes plenty of examples, diagrams, and screenshots to help you grasp the concepts quickly and easily.What You Will LearnUse Java for the development of neural network applicationsPrepare data for many different tasksCarry out some unusual neural network processingUse a neural network to process non-continuous functionsDevelop a program that recognizes handwritten digitsWho This Book Is ForIntermediate machine learning and deep learning developers who are interested in switching to Java.