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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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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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Deep Learning and Practice with MindSpore

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;

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Deep Learning and Practice with MindSpore

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;

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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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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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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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State of the Art in Neural Networks and Their Applications

State of the Art in Neural Networks and Their Applications presents the latest advances in artificial neural networks and their;

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Hardware Architectures for Deep Learning

neural networks. The rapid growth of server, desktop, and embedded applications based on deep learning has brought about a;

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Neural Information Processing

submissions. The papers address the emerging topics of theoretical research, empirical studies, and applications of neural information processing;

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Python Deep Learning

foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications across;

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Handbook on Neural Information Processing

This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical;

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Introduction to Deep Learning Business Applications for Developers

video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL;

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Deep Learning for Data Analytics

analyze large volumes of data for business, engineering, and biomedical applications. Deep learning architectures including deep neural networks;

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MATLAB Deep Learning

, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB;

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Neural Networks with R

with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial;

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Hands-On Neural Networks

Design and create neural networks with deep learning and artificial intelligence principles using OpenAI Gym, TensorFlow, and Keras Key;

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Introduction to Deep Learning for Healthcare

This textbook presents deep learning models and their healthcare applications. It focuses on rich health data and deep learning models that;

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The Deep Learning with PyTorch Workshop

complexity of neural network architectures. The Deep Learning with PyTorch Workshop starts with an introduction to deep learning and its applications;

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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering;

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Advanced Deep Learning with R

learning book starts by covering the essential deep learning techniques and concepts for prediction and classification. You will learn about neural;

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Deep Learning on Edge Computing Devices

learning, including neural networks. The title helps researchers maximize the performance of Edge-deep learning models for mobile computing and;

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Principles Of Artificial Neural Networks

The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence;

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Deep Learning with R for Beginners

fundamentals of deep learning and neural networks Use R 3.5 and its libraries and APIs to build deep learning models for computer vision and text;

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R Deep Learning Projects

neural networks with helpful tips, tricks, and best practices Book DescriptionR is a popular programming language used by statisticians and;

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