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PyTorch Deep Learning Hands-On

Hands-on projects cover all the key deep learning methods built step-by-step in PyTorch Key Features Internals and principles of PyTorch;

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Hands-on Machine Learning with Python

third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks;

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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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Hands-on Machine Learning with Python

third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks;

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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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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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Artificial Neural Networks

pitfalls. Authoritative and practical, Artificial Neural Networks: Third Edition should be of value to all scientists interested in the hands-on;

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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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Practical Deep Learning

concepts such as classes and labels, building a dataset, and what a model is and does before presenting classic machine learning models, neural;

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Neural Networks for Complete Beginners

architecture of an artificial neural network. The various types of artificial neural networks based on their architecture are also discussed. The book;

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Deep Learning with Python

Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory;

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Deep Learning with Python

Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory;

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Neural Network Programming with Java

makes neural networks behave in the same manner as the brain of human beings. This process is discussed in this book. You are also guided on how;

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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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Reinforcement Learning for Finance

library. Reinforcement Learning for Finance begins by describing methods for training neural networks. Next, it discusses CNN and RNN - two;

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Neural Network Programming with Python

This book is a guide on how to implement a neural network in the Python programming language. It begins by giving you a brief overview;

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Hands-On Deep Learning with Apache Spark

learning with Apache Spark Train neural networks with deep learning libraries such as BigDL and TensorFlow Develop Spark deep learning applications;

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Advanced Models of Neural Networks

This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by;

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

algorithms with pulldown menus. This hands-on tutorial demonstrates both neural networks and fuzzy-logic control with a different approach. A natural;

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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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Circuit Complexity and Neural Networks

Neural networks usually work adequately on small problems but can run into trouble when they are scaled up to problems involving large;

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Evolutionary Algorithms and Neural Networks

This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At;

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Guide to Convolutional Neural Networks

This must-read text/reference introduces the fundamental concepts of convolutional neural networks (ConvNets), offering practical guidance;

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Guide to Convolutional Neural Networks

This must-read text/reference introduces the fundamental concepts of convolutional neural networks (ConvNets), offering practical guidance;

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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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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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Complex-valued Neural Networks

-ever book on complex-valued neural networks, the most active scientists at the forefront of the field describe theories and applications from;

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