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On-Line Learning in Neural Networks

analysis of on-line learning. An introduction relates the subject to other developments in neural networks and explains the overall picture;

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On-Line Learning in Neural Networks

analysis of on-line learning. An introduction relates the subject to other developments in neural networks and explains the overall picture;

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Engineering Applications of Neural Networks

This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN;

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Neural Networks for Complete Beginners

concept of learning which is common in human beings. This book guides you to understand how learning takes place in artificial neural networks;

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Advanced Deep Learning with Python

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural;

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Deep Neural Networks and Applications

to main neural networks (MNN). The book throws light on the prospect of artificial intelligence and the applications it has in risk;

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Recurrent Neural Networks for Prediction

, data--reusing adaptation, and normalisation ? Studies convergence and stability of on--line learning algorithms based upon optimisation;

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Handbook on Neural Information Processing

Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for structured data Multiple;

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

applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities-and provides co-design and;

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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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Neural Network Programming with Java

neural networks are. You will learn how they operate. The process of learning in neural networks is very important. This is the concept which;

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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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Evolutionary Machine Learning Techniques

This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded;

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Evolutionary Machine Learning Techniques

This book provides an in-depth analysis of the current evolutionary machine learning techniques. Discussing the most highly regarded;

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Artificial Neural Networks and Machine Learning - ICANN 2017

The two volume set, LNCS 10613 and 10614, constitutes the proceedings of then 26th International Conference on Artificial Neural Networks;

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Artificial Neural Networks and Machine Learning - ICANN 2017

The two volume set, LNCS 10613 and 10614, constitutes the proceedings of then 26th International Conference on Artificial Neural Networks;

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Kinematic Control of Redundant Robot Arms Using Neural Networks

neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for;

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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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Supervised Learning with Complex-valued Neural Networks

complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This;

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Deep Learning and Artificial Intelligence

Welcome to this book on Deep Learning and Neural Networks. We're going to be diving into what neural networks are, what the current neural;

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Deep Learning and Artificial Intelligence

Welcome to this book on Deep Learning and Neural Networks. We're going to be diving into what neural networks are, what the current neural;

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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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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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Hands-on Machine Learning with Python

. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch. After completing Hands-on Machine Learning with;

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Hands-On Neural Networks

financial forecasting, and even machine diagnostics. Hands-On Neural Networks is designed to guide you through learning about neural networks in a;

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Neural Network Methods in Natural Language Processing

Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data;

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Neural Network Methods in Natural Language Processing

Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data;

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