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This Handbook aims to serve as a one-stop, reliable resource, including curated surveys and expository contributions on Federated Learning. It covers a comprehensive range of topics, providing the reader with technical and non-technical fundamentals, applications, and extensive details of various topics. The readership spans from researchers and academics to practitioners who are deeply engaged or are starting to venture into the realms of Trustworthy Federated Learning. First introduced in 2016, federated learning allows devices to collaboratively learn a shared model while keeping raw data localized, thus promising to protect data privacy. Since its introduction, federated learning has undergone several evolutions. Most importantly, its evolution is in response to the growing recognition that its promise of collaborative learning is inseparable from the imperatives of privacy preservation and model security. The resource is divided into four parts. Part 1 (Security and Privacy) explores the robust defense mechanisms against targeted attacks and addresses fairness concerns, providing a multifaceted foundation for securing Federated Learning systems against evolving threats. Part 2 (Bilevel Optimization) unravels the intricacies of optimizing performance in federated settings. Part 3 (Graph and Large Language Models) addresses the challenges in training Graph Neural Networks and ensuring privacy in Federated Learning of natural language models. Part 4 (Edge Intelligence and Applications) demonstrates how Federated Learning can empower mobile applications and preserve privacy with synthetic data.

Machine learning. --- Federated database systems.

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This book offers in 27 chapters a collection of all the technical aspects of specifying, developing, and evaluating the theoretical underpinnings and applied mechanisms of AI tools. Topics covered include neural networks, fuzzy controls, decision trees, rule-based systems, data mining, genetic algorithm and agent systems, among many others. The goal of this book is to show some potential applications and give a partial picture of the current state-of-the-art of AI. Also, it is useful to inspire some future research ideas by identifying potential research directions. It is dedicated to students, researchers and practitioners in this area or in related fields.

Databases. --- Data banks --- Data bases --- Databanks --- Database systems --- Computer files --- Electronic information resources --- Databases

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With their latest product, SAP S/4HANA, SAP is revolutionizing how we approach finance by re-architecting data persistency and merging accounts and cost elements. This book offers a fundamental introduction to SAP S/4HANA Finance. Dive into the three pillars of innovation including SAP Accounting powered by SAP HANA, SAP Cash Management, and SAP BI Integrated Planning. Find out about the new configuration options, updated data model, and what this means for reporting in the future. Geta first-hand look at the new user interfaces in SAP Fiori. Review new universal journal, asset accounting, material ledger, and account-based profitability analysis functionality. Examine the steps required to migrate to SAP S/4HANA Finance and walk through the deployment options. By using practical examples, tips, and screenshots, this book helps readers to:- Understand the basics of SAP S/4 Finance - Explore the new architecture, configuration options, and SAP Fiori - Examine SAP S/4 Finance migration steps - Assess the impact on business processes

Finance --- Databases --- Data banks --- Data bases --- Databanks --- Database systems --- Computer files --- Electronic information resources --- Data processing --- E-books

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This book takes you on a fantastic journey to discover the attributes of big data using Apache Hive. About This Book Grasp the skills needed to write efficient Hive queries to analyze the Big Data Discover how Hive can coexist and work with other tools within the Hadoop ecosystem Uses practical, example-oriented scenarios to cover all the newly released features of Apache Hive 2.3.3 Who This Book Is For If you are a data analyst, developer, or simply someone who wants to quickly get started with Hive to explore and analyze Big Data in Hadoop, this is the book for you. Since Hive is an SQL-like language, some previous experience with SQL will be useful to get the most out of this book. What You Will Learn Create and set up the Hive environment Discover how to use Hive's definition language to describe data Discover interesting data by joining and filtering datasets in Hive Transform data by using Hive sorting, ordering, and functions Aggregate and sample data in different ways Boost Hive query performance and enhance data security in Hive Customize Hive to your needs by using user-defined functions and integrate it with other tools In Detail In this book, we prepare you for your journey into big data by frstly introducing you to backgrounds in the big data domain, alongwith the process of setting up and getting familiar with your Hive working environment. Next, the book guides you through discovering and transforming the values of big data with the help of examples. It also hones your skills in using the Hive language in an effcient manner. Toward the end, the book focuses on advanced topics, such as performance, security, and extensions in Hive, which will guide you on exciting adventures on this worthwhile big data journey. By the end of the book, you will be familiar with Hive and able to work effeciently to find solutions to big data problems Style and approach This book takes on a practical approach which will get you familiarized with Apache Hive and how to use it to efficiently to find solutions to your big data problems. This book covers crucial topics like performance, and data security in order to help you make the most of the Hive working environment. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-ma...

Databases --- Data banks --- Data bases --- Databanks --- Database systems --- Computer files --- Electronic information resources --- Design --- Data processing. --- Apache Hadoop. --- Hadoop

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Run blazingly fast queries on complex graph datasets with the power of the Neo4j graph database In Detail Learning Neo4j provides you with a step-by-step approach of adopting Neo4j, the world's leading graph database. This book includes a lot of background information, helps you grasp the fundamental concepts behind this radical new way of dealing with connected data, and will give you lots of examples of use cases and environments where a graph database would be a great fit. Starting with a brief introduction to graph theory, this book will show you the advantages of using graph databases. Following on from that, you will be introduced to Neo4j and you will be shown how to install Neo4j on various operating systems. You will then be shown how you can model and import your data into Neo4j. This book has two use case examples that will show you how to model and implement a graph in Neo4j by analyzing a user case, and analyze the impact a change has on a process or a system. You will also gain an insight into graph visualization options for Neo4j and discover external sources where you can learn more about Neo4j. What You Will Learn Background and specifications of graph databases Install Neo4j on a variety of different platforms, locally and in the cloud Model data for a graph database such as Neo4j Import data into Neo4j Learn about sample use cases for Neo4j Discover the advantages of graph databases versus other database models Find out where you can find additional information on Neo4j

Database design. --- Databases --- Data banks --- Data bases --- Databanks --- Database systems --- Computer files --- Electronic information resources --- Data base design --- System design --- Development. --- Programming.