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Edité par Bentham Science Publishers, 2023
ISBN 10 : 981516581X ISBN 13 : 9789815165814
Langue: anglais
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Edité par Bentham Science Publishers, 2023
ISBN 10 : 981516581X ISBN 13 : 9789815165814
Langue: anglais
Vendeur : California Books, Miami, FL, Etats-Unis
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Ajouter au panierPaperback. Etat : new. Paperback. Are you ready to transform your understanding of AI and unlock the power of Federated Learning? In a world where data privacy is paramount, this breakthrough approach to training machine learning models across devices-without sharing raw data-is revolutionizing the future of artificial intelligence.Federated Learning in Practice: Training Across Devices Without Sharing Raw Data is the ultimate guide for anyone looking to master this cutting-edge technique. Whether you're a machine learning engineer, a privacy-conscious developer, or simply someone interested in the future of AI, this book will equip you with the knowledge and practical skills to build secure, scalable, and privacy-preserving machine learning systems.Inside, you'll learn: The fundamentals of federated learning and why it's the key to privacy-first AIHow to implement federated learning systems across devices and environmentsStrategies to overcome challenges like data heterogeneity, device dropout, and unreliable networksTechniques to protect sensitive data using secure aggregation and differential privacyReal-world case studies from industries like healthcare, finance, and mobile AIPractical, hands-on examples and code in Python with frameworks like TensorFlow Federated and PySyftThis book isn't just theory-it's a step-by-step roadmap that will show you how to take your AI projects from concept to deployment. You'll walk away with the tools and confidence to create models that learn collaboratively, while keeping user data private and secure.The future of AI is decentralized, privacy-focused, and more powerful than ever. Don't get left behind-buy this book now and learn how to be part of the next wave of innovation in machine learning. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Edité par Springer Nature Switzerland, 2022
ISBN 10 : 3031185226 ISBN 13 : 9783031185229
Langue: anglais
Vendeur : Buchpark, Trebbin, Allemagne
EUR 39,79
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Ajouter au panierEtat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.
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Vendeur : California Books, Miami, FL, Etats-Unis
EUR 45,73
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Edité par Springer Nature Switzerland, 2025
ISBN 10 : 3031822390 ISBN 13 : 9783031822391
Langue: anglais
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
EUR 52,08
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Ajouter au panierPAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.
Edité par Springer International Publishing AG, 2025
ISBN 10 : 3031822390 ISBN 13 : 9783031822391
Langue: anglais
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
EUR 48,85
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Ajouter au panierPAP. Etat : New. New Book. Shipped from UK. Established seller since 2000.
Edité par Packt Publishing 10/28/2022, 2022
ISBN 10 : 180324710X ISBN 13 : 9781803247106
Langue: anglais
Vendeur : BargainBookStores, Grand Rapids, MI, Etats-Unis
EUR 43,78
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Ajouter au panierPaperback or Softback. Etat : New. Federated Learning with Python: Design and implement a federated learning system and develop applications using existing frameworks. Book.
Edité par Springer International Publishing, 2023
ISBN 10 : 3031289951 ISBN 13 : 9783031289958
Langue: anglais
Vendeur : Buchpark, Trebbin, Allemagne
EUR 43,92
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Ajouter au panierEtat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 52,72
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Edité par Packt Publishing Limited, GB, 2022
ISBN 10 : 180324710X ISBN 13 : 9781803247106
Langue: anglais
Vendeur : Rarewaves.com UK, London, Royaume-Uni
EUR 55,21
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Ajouter au panierPaperback. Etat : New. Learn the essential skills for building an authentic federated learning system with Python and take your machine learning applications to the next levelKey FeaturesDesign distributed systems that can be applied to real-world federated learning applications at scaleDiscover multiple aggregation schemes applicable to various ML settings and applicationsDevelop a federated learning system that can be tested in distributed machine learning settingsBook DescriptionFederated learning (FL) is a paradigm-shifting technology in AI that enables and accelerates machine learning (ML), allowing you to work on private data. It has become a must-have solution for most enterprise industries, making it a critical part of your learning journey. This book helps you get to grips with the building blocks of FL and how the systems work and interact with each other using solid coding examples.FL is more than just aggregating collected ML models and bringing them back to the distributed agents. This book teaches you about all the essential basics of FL and shows you how to design distributed systems and learning mechanisms carefully so as to synchronize the dispersed learning processes and synthesize the locally trained ML models in a consistent manner. This way, you'll be able to create a sustainable and resilient FL system that can constantly function in real-world operations. This book goes further than simply outlining FL's conceptual framework or theory, as is the case with the majority of research-related literature.By the end of this book, you'll have an in-depth understanding of the FL system design and implementation basics and be able to create an FL system and applications that can be deployed to various local and cloud environments.What you will learnDiscover the challenges related to centralized big data ML that we currently face along with their solutionsUnderstand the theoretical and conceptual basics of FLAcquire design and architecting skills to build an FL systemExplore the actual implementation of FL servers and clientsFind out how to integrate FL into your own ML applicationUnderstand various aggregation mechanisms for diverse ML scenariosDiscover popular use cases and future trends in FLWho this book is forThis book is for machine learning engineers, data scientists, and artificial intelligence (AI) enthusiasts who want to learn about creating machine learning applications empowered by federated learning. You'll need basic knowledge of Python programming and machine learning concepts to get started with this book.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 53,89
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
EUR 41,45
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Edité par Bentham Science Publishers, 2024
ISBN 10 : 9815313045 ISBN 13 : 9789815313048
Langue: anglais
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
EUR 55,03
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Ajouter au panierpaperback. Etat : New.
Edité par Bentham Science Publishers, 2023
ISBN 10 : 981516581X ISBN 13 : 9789815165814
Langue: anglais
Vendeur : Best Price, Torrance, CA, Etats-Unis
EUR 34,59
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Edité par Springer International Publishing AG, CH, 2025
ISBN 10 : 3031822390 ISBN 13 : 9783031822391
Langue: anglais
Vendeur : Rarewaves.com UK, London, Royaume-Uni
EUR 59,36
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Ajouter au panierPaperback. Etat : New. This LNAI volume constitutes the post proceedings of International Federated Learning Workshops such as follows:FL@FM-WWW 2024, FL@FM-ICME 2024, FL@FM-IJCAI 2024 and FL@FM-NeurIPS 2024. This LNAI volume focuses on the following topics:Efficient Model Adaptation and Personalization, Data Heterogeneity and Incomplete Data, Integration of Specialized Neural Architectures, Frameworks and Tools for Federated Learning, Applications in Domain-Specific Contexts, Unsupervised and Lightweight Learning, and Causal Discovery and Black-Box Optimization.
Edité par Packt Publishing Limited, GB, 2022
ISBN 10 : 180324710X ISBN 13 : 9781803247106
Langue: anglais
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
EUR 60,02
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Ajouter au panierPaperback. Etat : New. Learn the essential skills for building an authentic federated learning system with Python and take your machine learning applications to the next levelKey FeaturesDesign distributed systems that can be applied to real-world federated learning applications at scaleDiscover multiple aggregation schemes applicable to various ML settings and applicationsDevelop a federated learning system that can be tested in distributed machine learning settingsBook DescriptionFederated learning (FL) is a paradigm-shifting technology in AI that enables and accelerates machine learning (ML), allowing you to work on private data. It has become a must-have solution for most enterprise industries, making it a critical part of your learning journey. This book helps you get to grips with the building blocks of FL and how the systems work and interact with each other using solid coding examples.FL is more than just aggregating collected ML models and bringing them back to the distributed agents. This book teaches you about all the essential basics of FL and shows you how to design distributed systems and learning mechanisms carefully so as to synchronize the dispersed learning processes and synthesize the locally trained ML models in a consistent manner. This way, you'll be able to create a sustainable and resilient FL system that can constantly function in real-world operations. This book goes further than simply outlining FL's conceptual framework or theory, as is the case with the majority of research-related literature.By the end of this book, you'll have an in-depth understanding of the FL system design and implementation basics and be able to create an FL system and applications that can be deployed to various local and cloud environments.What you will learnDiscover the challenges related to centralized big data ML that we currently face along with their solutionsUnderstand the theoretical and conceptual basics of FLAcquire design and architecting skills to build an FL systemExplore the actual implementation of FL servers and clientsFind out how to integrate FL into your own ML applicationUnderstand various aggregation mechanisms for diverse ML scenariosDiscover popular use cases and future trends in FLWho this book is forThis book is for machine learning engineers, data scientists, and artificial intelligence (AI) enthusiasts who want to learn about creating machine learning applications empowered by federated learning. You'll need basic knowledge of Python programming and machine learning concepts to get started with this book.
Edité par Bentham Science Publishers, 2024
ISBN 10 : 9815313045 ISBN 13 : 9789815313048
Langue: anglais
Vendeur : California Books, Miami, FL, Etats-Unis
EUR 55,41
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