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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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Pattern Recognition with Neural Networks in C++

toward the practitioner, Pattern Recognition with Neural Networks in C++ covers pattern classification and neural network approaches within the;

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Pattern Recognition with Neural Networks in C++

toward the practitioner, Pattern Recognition with Neural Networks in C++ covers pattern classification and neural network approaches within the;

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Kinematic Control of Redundant Robot Arms Using Neural Networks

Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks This book;

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Hands-On Deep Learning with TensorFlow

convoluted neural networks, then this book is for you. Some familiarity with C++ or Python is assumed. What You Will Learn * Set up your;

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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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Recent Advances in Artificial Neural Networks

students from all disciplines with an interest in considering neural networks for solving real-world problems will find this collection useful.;

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Neural Networks and Fuzzy Logic

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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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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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Artificial Neural Networks: Formal Models and Their Applications - ICANN 2005

This volume is the first part of the two-volume proceedings of the International C- ference on Artificial Neural Networks (ICANN 2005;

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Exploring Cognition: Damaged Brains and Neural Networks

Exploring Cognition: Damaged Brains and Neural Networks analyses the contribution made by cognitive neuropsychology and connectionist;

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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural;

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Neural Networks with R

in neural networks with R, to implement them in your applications * Build smart systems using the power of deep learning * Real-world case studies;

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Simulating Neural Networks with Mathematica

implement and experiment with neural network architectures. *Addresses a major topic related to neural networks in each chapter, or a specific type;

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Deep Learning from Scratch Building with Python from First Principles

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many;

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Complex-Valued Neural Networks

This book covers the hot topics and applications surrounding complex-valued neural networks. It demonstrates advanced theories with a wide;

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Computational Intelligence Paradigms

neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous;

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Computational Intelligence Paradigms

neural networks, fuzzy systems, evolutionary computation, genetic algorithms and programming, and swarm intelligence. It covers numerous;

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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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Complex-valued Neural Networks

-Dimensional Parameters covers the current state-of-the-art theories and applications of neural networks with high-dimensional parameters such as;

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Stochastic Models of Neural Networks

and very promising model of human brain neural activity consistent with the need of learning from a stochastic environment. Moreover, the;

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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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Statistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;

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Statistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;

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Neural Network Programming with Python

network works is also explored. You are then guided on how to implement neural networks with Neupy, another Python library.The following topics;

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