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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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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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Principles Of Artificial Neural Networks (2nd Edition)

The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering;

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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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Exploring Neural Networks with C#

Networks with C# presents the important properties of neural networks-while keeping the complex mathematics to a minimum. Explaining how to build;

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Exploring Neural Networks with C#

Networks with C# presents the important properties of neural networks while keeping the complex mathematics to a minimum. Explaining how to build;

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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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Pattern Recognition with Neural Networks in C++

book beneficial. Pattern Recognition with Neural Networks in C++ is also suitable for courses in neural networks at an advanced undergraduate;

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Pattern Recognition with Neural Networks in C++

book beneficial. Pattern Recognition with Neural Networks in C++ is also suitable for courses in neural networks at an advanced undergraduate;

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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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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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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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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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Neural Networks for Control

Neural Networks for Control highlights key issues in learning control and identifies research directions that could lead to practical;

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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 for Optimization and Signal Processing

A topical introduction on the ability of artificial neural networks to not only solve on-line a wide range of optimization problems but;

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Naturally Intelligent Systems

new entry in this arena - neural networks. Naturally Intelligent Systems offers a comprehensive introduction to these exciting systems. It;

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Recent Advances in Artificial Neural Networks

* Provides up-to-date coverage of neural network paradigms and applications* Presents the work of internationally renowned experts;

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Neural Networks and Statistical Learning

This book provides a broad yet detailed introduction to neural networks and machine learning in a statistical framework. A single;

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Learning in Energy-Efficient Neuromorphic Computing - Algorithm and Architecture Co-Design

comes an introduction to various options for executing neural networks, ranging from general-purpose processors to specialized hardware, from;

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Introduction to Graph Neural Networks

comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN;

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Introduction to Graph Neural Networks

This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with;

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An Introduction to Neural Network Methods for Differential Equations

comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their;

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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise;

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Neural Nets And Chaotic Carriers (2nd Edition)

Neural Nets and Chaotic Carriers develops rational principles for the design of associative memories, with a view to applying these;

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