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Edité par Packt Publishing 2018-03, 2018
ISBN 10 : 1788831101 ISBN 13 : 9781788831109
Langue: anglais
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Ajouter au panierEtat : New. This book introduces the core concepts of deep learning. Get implementation and research details on cutting-edge architectures and apply advanced concepts to your own projects. Develop your knowledge of deep neural networks through hands-on model building a.
Edité par Packt Publishing Limited, 2018
ISBN 10 : 1788831101 ISBN 13 : 9781788831109
Langue: anglais
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
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Ajouter au panierPAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Edité par Packt Publishing Limited, 2018
ISBN 10 : 1788831101 ISBN 13 : 9781788831109
Langue: anglais
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Ajouter au panierPAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.Key FeaturesLearn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlowExplore deep neural networks and layers of data abstraction with the help of this comprehensive guideGain real-world contextualization through some deep learning problems concerning research and applicationBook DescriptionDeep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks.This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries.Throughout the book, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way.You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects.What you will learnApply deep machine intelligence and GPU computing with TensorFlowAccess public datasets and use TensorFlow to load, process, and transform the dataDiscover how to use the high-level TensorFlow API to build more powerful applicationsUse deep learning for scalable object detection and mobile computingTrain machines quickly to learn from data by exploring reinforcement learning techniquesExplore active areas of deep learning research and applications.