Artificial Neural Networks with Java: Tools for Building Neural Network Applications
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 understan...
Gespeichert in:
Beteilige Person: | |
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Format: | Elektronisch E-Book |
Sprache: | Englisch |
Veröffentlicht: |
Berkeley, CA
Apress L. P.
2021
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Ausgabe: | 2nd ed. |
Schlagwörter: | |
Links: | https://learning.oreilly.com/library/view/-/9781484273685/?ar |
Zusammenfassung: | 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 Learn Use Java for the development of neural network applications Prepare data for many different tasks Carry out some unusual neural network processing Use a neural network to process non-continuous functions Develop a program that recognizes handwritten digits Who This Book Is For Intermediate machine learning and deep learning developers who are interested in switching to Java. |
Beschreibung: | Description based upon print version of record. - Reflecting Function Topology in the Data |
Umfang: | 1 Online-Ressource (635 Seiten) |
ISBN: | 9781484273685 1484273680 |
Internformat
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discipline | Informatik |
edition | 2nd ed. |
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spelling | Livshin, Igor VerfasserIn aut Artificial Neural Networks with Java Tools for Building Neural Network Applications 2nd ed. Berkeley, CA Apress L. P. 2021 1 Online-Ressource (635 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Description based upon print version of record. - Reflecting Function Topology in the Data 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 Learn Use Java for the development of neural network applications Prepare data for many different tasks Carry out some unusual neural network processing Use a neural network to process non-continuous functions Develop a program that recognizes handwritten digits Who This Book Is For Intermediate machine learning and deep learning developers who are interested in switching to Java. Neural networks (Computer science) Java (Computer program language) Neural Networks, Computer Réseaux neuronaux (Informatique) Java (Langage de programmation) 9781484273678 Erscheint auch als Druck-Ausgabe 9781484273678 |
spellingShingle | Livshin, Igor Artificial Neural Networks with Java Tools for Building Neural Network Applications Neural networks (Computer science) Java (Computer program language) Neural Networks, Computer Réseaux neuronaux (Informatique) Java (Langage de programmation) |
title | Artificial Neural Networks with Java Tools for Building Neural Network Applications |
title_auth | Artificial Neural Networks with Java Tools for Building Neural Network Applications |
title_exact_search | Artificial Neural Networks with Java Tools for Building Neural Network Applications |
title_full | Artificial Neural Networks with Java Tools for Building Neural Network Applications |
title_fullStr | Artificial Neural Networks with Java Tools for Building Neural Network Applications |
title_full_unstemmed | Artificial Neural Networks with Java Tools for Building Neural Network Applications |
title_short | Artificial Neural Networks with Java |
title_sort | artificial neural networks with java tools for building neural network applications |
title_sub | Tools for Building Neural Network Applications |
topic | Neural networks (Computer science) Java (Computer program language) Neural Networks, Computer Réseaux neuronaux (Informatique) Java (Langage de programmation) |
topic_facet | Neural networks (Computer science) Java (Computer program language) Neural Networks, Computer Réseaux neuronaux (Informatique) Java (Langage de programmation) |
work_keys_str_mv | AT livshinigor artificialneuralnetworkswithjavatoolsforbuildingneuralnetworkapplications |