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Introduction to Neural Networks for Java, Second Edition

"Introduction to Neural Networks for Java" introduces the Java programmer to the world of Neural Networks and Artificial Intelligence;

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Artificial Neural Networks with Java

regression, this second edition shows you how to use neural networks for computer vision. It focuses on image recognition such as the classification;

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Neural Network Programming with Java

This book is an exploration of neural networks and how to implement them in Java. First, the reader is guided so as to understand what;

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Artificial Neural Networks with Java

discussed in the book is using Java for neural network processing. You will use the Encog Java framework and discover how to do rapid development;

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Artificial Neural Networks with Java

discussed in the book is using Java for neural network processing. You will use the Encog Java framework and discover how to do rapid development;

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Neural Networks

Neural Networks, Second Edition provides a complete introduction to neural networks. It describes what they are, what they can do, and how;

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Java Deep Learning Cookbook

library for training neural networks efficiently. This book starts by showing you how to install and configure Java and DL4J on your system. You;

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Introduction to Neural Networks for C#, 2nd Edition

This resource introduces the C# programmer to the world of Neural Networks and Artificial Intelligence. Training techniques, such as;

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Java by Dissection

Second Edition. Introduction to programming using Java.;

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Artificial Neural Networks with Java

Intermediate-Advanced user level;...

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Neural Networks: Tricks of the Trade

The twenty last years have been marked by an increase in available data and computing power. In parallel to this trend, the focus of neural;

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Java and Object Orientation

This second edition shows readers how to build object oriented applications in Java. Written in a clear and concise style, with lots;

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Introduction to Deep Learning and Neural Networks with PythonT

Introduction to Deep Learning and Neural Networks with PythonT: A Practical Guide is an intensive step-by-step guide for neuroscientists to;

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An Introduction to Network Programming with Java

Since the second edition of this text, the use of the Internet and networks generally has continued to expand at a phenomenal rate. This;

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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

will be a quick introduction to using Cognitive Toolkit and will teach you how to train and validate different types of neural networks, such;

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Fundamentals Neural NetworksUnited State

An exceptionally clear, thorough introduction to neural networks written at an elementary level. Written with the beginning student in mind;

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Blind Equalization in Neural Networks

The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms;

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Deep Learning from Scratch Building with Python from First Principles

networks Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework Working;

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Complex-Valued Neural Networks

This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published;

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Principles Of Artificial Neural Networks

course on artificial neural networks. It is also intended to be a self-study and a reference text for scientists, engineers and for researchers;

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An Introduction to the Modeling of Neural Networks

This text is a beginning graduate-level introduction to neural networks, focussing on current theoretical models, examining what these;

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Neural Networks and Animal Behavior

accessible to nonspecialists. The first chapter introduces various approaches to animal behavior and provides an informal introduction to neural;

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Statistical Mechanics of Neural Networks

This book highlights a comprehensive introduction to the fundamental statistical mechanics underneath the inner workings of neural networks;

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Mathematical Tools In Signal Processing With C++ And Java Simulations

developed for the processing, transformation, and interpretation of signals. This book provides a comprehensive introduction to the traditional and;

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Neural Networks for Applied Sciences and Engineering

In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering;

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Neural Networks And Brain Function

network. The second section describes real neural networks in several brain systems, and shows how it is becoming possible to construct theories;

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Deep Learning

you solve real-world problems and links neural network theory to their application Who This Book Is For This course is intended for data;

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