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Neural Networks Without the Math

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Introduction to Deep Learning and Neural Networks with PythonT

fully understand, practice, and build neural networks. Providing math and PythonT code examples to clarify neural network calculations, by;

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Advanced Deep Learning with Python

LSTM and GRU. You'll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs;

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Neural Networks and Animal Behavior

how ANNs can be investigated by math and by computers. They demonstrate intuitive concepts that make the operation of neural networks more;

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Artificial Neural Networks

This tutorial text provides the reader with an understanding of artificial neural networks (ANNs), and their application, beginning with;

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Neural Networks & Fuzzy-Logic Control On Personal Computers & Workstations + D3

on the screen; real simulation experiments then execute immediately.Neural Networks and Fuzzy-Logic Control introduces a;

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Artificial Neural Networks

-layered learning network based on simple math rules. The structure of an artificial neural network consists of an input layer, an output layer and;

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Artificial Neural Network Modeling of Water & Wastewater Treatments Processes

Artificial neural networks (ANNs) are computer based systems that are designed to simulate the learning process of neurons in the human;

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New Developments In Artificial Neural Networks Research

This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include a;

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Focus on Artificial Neural Networks

This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include;

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Neural Networks for Complete Beginners

This book is an exploration of an artificial neural network. It has been created to suit even the complete beginners to artificial neural;

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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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Evolutionary Machine Learning Techniques

networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews;

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Evolutionary Machine Learning Techniques

networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions;

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Kinematic Control of Redundant Robot Arms Using Neural Networks

specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations;

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Applied Neural Networks and Soft Computing

Applied Neural Networks and Soft Computing examines the relation between neural networks and soft computing. Neural network is a system;

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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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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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Information-Theoretic Aspects of Neural Networks

sparsely cover the entropy and/or cybernetic aspects of neural information. Information-Theoretic Aspects of Neural Networks cohesively explores;

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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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Neural Networks with R

Uncover the power of artificial neural networks by implementing them through R code. About This Book * Develop a strong background;

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Simulating Neural Networks with Mathematica

This book introduces neural networks, their operation, and application, in the context of the interactive Mathematica environment. Readers;

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Neural Information Processing

The seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing;

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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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Spatially Explicit Hyperparameter Optimization for Neural Networks

Neural networks as the commonly used machine learning algorithms, such as artificial neural networks (ANNs) and convolutional neural;

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Learn Keras for Deep Neural Networks

Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses;

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Neural Networks And Brain Function

The aim of this book is to describe the types of computation that can be performed by biologically plausible neural networks, and to show;

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