Programming Neural Networks with Encog 3 in Java
Programming Neural Networks with Encog 3 in Java

Author: Jeff Heaton

Publisher:

Published: 2011

Total Pages: 242

ISBN-13: 9781604390216

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Beginning where our introductory neural network programing book left off, this book introduces you to Encog. Encog allows you to focus less on the actual implementation of neural networks and focus on how to use them. Encog is an advanced neural network programming framework that allows you to create a variety of neural network architectures using the Java programming language. Neural network architectures such as feedforward/perceptrons, Hopfield, Elman, Jordan, Radial Basis Function, and Self Organizing maps are all demonstrated. This book also shows how to use Encog to train neural networks using a variety of means. Several propagation techniques, such as back propagation, resilient propagation (RPROP) and the Manhattan update rule are discussed. Additionally, training with a genetic algorithm and simulated annealing is discussed as well. You will also see how to enhance training using techniques such as pruning and hybrid training.

Programming Neural Networks with Encog 2 in Java
Programming Neural Networks with Encog 2 in Java

Author: Jeff Heaton

Publisher:

Published: 2009-12

Total Pages: 0

ISBN-13: 9781604390070

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Encog is an advanced neural network and bot programming framework. This book focuses on using Encog to create a variety of neural network architectures using the Java programming language. Neural network architectures such as feedforward/perceptrons, Hopfield, Elman, Jordan, Radial Basis Function, and Self Organizing maps are all demonstrated. This book also shows how to use Encog to train neural networks using a variety of means. Several propagation techniques, such as back propagation, resilient propagation (RPROP) and the Manhattan update rule are discussed. Additionally, training with a genetic algorithm and simulated annealing is discussed as well. You will also see how to enhance training using techniques such as pruning, hybrid training, Real world examples tie the book together. Pattern recognition applications such as OCR, image and text recognition will be introduced. You will see how to apply time series and forecasting and how to financial markets. All of the Encog neural network components will be demonstrated to show how to use them in your own neural network applications.

Introduction to Neural Networks with Java
Introduction to Neural Networks with Java

Author: Jeff Heaton

Publisher: Heaton Research Incorporated

Published: 2005

Total Pages: 380

ISBN-13: 097732060X

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In addition to showing the programmer how to construct Neural Networks, the book discusses the Java Object Oriented Neural Engine (JOONE), a free open source Java neural engine. (Computers)

Computer Information Systems and Industrial Management
Computer Information Systems and Industrial Management

Author: Khalid Saeed

Publisher: Springer

Published: 2013-09-20

Total Pages: 541

ISBN-13: 3642409253

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This book constitutes the proceedings of the 12th IFIP TC 8 International Conference, CISIM 2013, held in Cracow, Poland, in September 2013. The 44 papers presented in this volume were carefully reviewed and selected from over 60 submissions. They are organized in topical sections on biometric and biomedical applications; pattern recognition and image processing; various aspects of computer security, networking, algorithms, and industrial applications. The book also contains full papers of a keynote speech and the invited talk.

Artificial Intelligence for Humans
Artificial Intelligence for Humans

Author: Jeff Heaton

Publisher: Createspace Independent Publishing Platform

Published: 2015

Total Pages: 0

ISBN-13: 9781505714340

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« Artifical Intelligence for Humans is a book series meant to teach AI to those readers who lack an extensive mathematical background. The reader only needs knowledge of basic college algebra and computer programming. Additional topics are thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, and Python. Other languages are planned. »--

Artificial Intelligence for Humans, Volume 2
Artificial Intelligence for Humans, Volume 2

Author: Jeff Heaton

Publisher: CreateSpace

Published: 2014-05-28

Total Pages: 242

ISBN-13: 9781499720570

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Nature can be a great source of inspiration for artificial intelligence algorithms because its technology is considerably more advanced than our own. Among its wonders are strong AI, nanotechnology, and advanced robotics. Nature can therefore serve as a guide for real-life problem solving. In this book, you will encounter algorithms influenced by ants, bees, genomes, birds, and cells that provide practical methods for many types of AI situations. Although nature is the muse behind the methods, we are not duplicating its exact processes. The complex behaviors in nature merely provide inspiration in our quest to gain new insights about data. Artificial Intelligence for Humans is a book series meant to teach AI to those readers who lack an extensive mathematical background. The reader only needs knowledge of basic college algebra and computer programming. Additional topics are thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, and Python. Other languages are planned. No knowledge of biology is needed to read this book. With a forward by Dave Snell.

Numeric Computation and Statistical Data Analysis on the Java Platform
Numeric Computation and Statistical Data Analysis on the Java Platform

Author: Sergei V. Chekanov

Publisher: Springer

Published: 2016-03-23

Total Pages: 635

ISBN-13: 3319285319

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Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis on the Java Platform is a great choice for those who want to learn how statistical data analysis can be done using popular programming languages, who want to integrate data analysis algorithms in full-scale applications, and deploy such calculations on the web pages or computational servers regardless of their operating system. It is an excellent reference for scientific computations to solve real-world problems using a comprehensive stack of open-source Java libraries included in the DataMelt (DMelt) project and will be appreciated by many data-analysis scientists, engineers and students.

Artificial Intelligence for Humans
Artificial Intelligence for Humans

Author: Jeff Heaton

Publisher: Createspace Independent Publishing Platform

Published: 2013

Total Pages: 0

ISBN-13: 9781493682225

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« Artifical Intelligence for Humans is a book series meant to teach AI to those readers who lack an extensive mathematical background. The reader only needs knowledge of basic college algebra and computer programming. Additional topics are thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, and Python. Other languages are planned. »--

Introduction to Neural Networks for C# (2nd Edition)
Introduction to Neural Networks for C# (2nd Edition)

Author: Jeff Heaton

Publisher: Heaton Research, Incorporated

Published: 2008

Total Pages: 0

ISBN-13: 9781604390094

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This resource introduces the C# programmer to the world of Neural Networks and Artificial Intelligence. Training techniques, such as backpropagation, genetic algorithms, and simulated annealing are also introduced.