Description: Federated Learning with Python by Kiyoshi Nakayama PhD, George Jeno Estimated delivery 3-12 business days Format Paperback Condition Brand New Description This book helps you understand how to design and implement a federated learning (FL) system. Using solid coding examples, youll be able to acquire the essential skills needed to develop and support machine learning applications empowered by FL that can protect data privacy, increase learning efficiency, and reduce computational resources and costs. Publisher Description 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, youll 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 FLs conceptual framework or theory, as is the case with the majority of research-related literature.By the end of this book, youll 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. Youll need basic knowledge of Python programming and machine learning concepts to get started with this book. Author Biography Kiyoshi Nakayama, PhD, is the founder and CEO of TieSet Inc., which leads the development and dissemination of one of the most advanced distributed and federated learning platforms in the world. Before founding TieSet, he was a research scientist at NEC Laboratories America, renowned for having the worlds top-notch machine learning research group of researchers. He was also a postdoctoral researcher at Fujitsu Laboratories of America, where he implemented a distributed system for smart energy. He has published several international articles and patents and received the best paper award twice in his career. Kiyoshi received his PhD in computer science from the University of California, Irvine.George Jeno is a co-founder of TieSet Inc. and has been a tech lead for the development of the STADLE federated learning platform. He has a deep understanding of machine learning theory and system architecture design, and he has leveraged this knowledge to research new algorithms and applications for distributed and federated learning. He holds a masters degree in computer science (with a specialization in machine learning) from Georgia Tech. Details ISBN 180324710X ISBN-13 9781803247106 Title Federated Learning with Python Author Kiyoshi Nakayama PhD, George Jeno Format Paperback Year 2022 Pages 326 Publisher Packt Publishing Limited GE_Item_ID:138816595; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. 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Price: 59.92 USD
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End Time: 2024-09-14T03:07:15.000Z
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ISBN-13: 9781803247106
Book Title: Federated Learning with Python
Publisher: Packt Publishing, The Limited
Subject: Machine Theory, Intelligence (Ai) & Semantics, Computer Science, General
Publication Year: 2022
Number of Pages: 326 Pages
Language: English
Publication Name: Federated Learning with Python : Design and Implement a Federated Learning System and Develop Applications Using Existing Frameworks
Type: Textbook
Subject Area: Computers, Science
Author: George Jeno
Format: Trade Paperback
