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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 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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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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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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Pattern Recognition and Neural Networks

Ripley brings together two crucial ideas in pattern recognition: statistical methods and machine learning via neural networks. He brings;

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Neural Networks with R

intelligence and deep learning and you want to level up, then this book is what you need! What You Will Learn * Set up R packages for neural;

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Neural Network Learning

learning problems, and addresses the key statistical and computational questions. Research on pattern classification with binary-output networks;

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Neural Network Learning

learning problems, and addresses the key statistical and computational questions. Research on pattern classification with binary-output networks;

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Evolutionary Machine Learning Techniques

methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning;

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Evolutionary Machine Learning Techniques

methods for classification, clustering, regression, and prediction, it includes techniques such as support vector machines, extreme learning;

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Mathematical Perspectives on Neural Networks

Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests;

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Mathematical Perspectives on Neural Networks

Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests;

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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 Networks For Pattern Recognition

detailed discussion of learning and generalization in neural networks, the book also covers the important topics of data processing, feature;

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Information-Theoretic Aspects of Neural Networks

neural network training non-conventional, statistical distance-measures for neural network optimizations symmetric and asymmetric;

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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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R Deep Learning Projects

mathematicians for statistical analysis, and is popularly used for deep learning. Deep Learning, as we all know, is one of the trending topics today, and;

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Deep Neural Networks and Applications

Deep Neural Networks and Applications makes the readers aware about the various artificial neural networks (ANN) and the topologies related;

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Statistics and Neural Networks

Recent years have seen a growing awareness of the interface between statistical research and recent advances in neural computing and;

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Engineering Applications of Neural Networks

machine, machine learning applications, predictive models, fuzzy and recommender systems, recurrent neural networks, spiking neural networks.;

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Modeling Brain Function

underlying brain function, this book introduces and explains the techniques brought from physics to the study of neural networks and the insights;

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Perturbations, Optimization, and Statistics

A description of perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical;

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New Developments In Artificial Neural Networks Research

neural network based visual servo system; modelling of computer-assisted learning using artificial neural networks; prediction of hole quality;

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Machine Learning

learning architectures. The book also covers the fundamentals of statistical parameter estimation, Wiener and Kalman filtering, convexity and;

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Computational Mechanics with Neural Networks

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other;

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Computational Mechanics with Neural Networks

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other;

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