Introduction To Data Governance For Machine Learning Systems
DOWNLOAD
Download Introduction To Data Governance For Machine Learning Systems PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Introduction To Data Governance For Machine Learning Systems book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Introduction To Data Governance For Machine Learning Systems
DOWNLOAD
Author : Aditya Nandan Prasad
language : en
Publisher: Springer Nature
Release Date : 2024-12-13
Introduction To Data Governance For Machine Learning Systems written by Aditya Nandan Prasad and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-13 with Mathematics categories.
This book is the first comprehensive guide to the intersection of data governance and machine learning (ML) projects. As ML applications proliferate, the quality, reliability, and ethical use of data is central to their success, which gives ML data governance unprecedented significance. However, adapting data governance principles to ML systems presents unique, complex challenges. Author Aditya Nandan Prasad equips you with the knowledge and tools needed to navigate this dynamic landscape effectively. Through this guide, you will learn to implement robust and responsible data governance practices, ensuring the development of sustainable, ethical, and future-proofed AI applications. The book begins by covering fundamental principles and practices of underlying ML applications and data governance before diving into the unique challenges and opportunities at play when adapting data governance theory and practice to ML projects, including establishing governance frameworks, ensuring data quality and interpretability, preprocessing, and the ethical implications of ML algorithms and techniques, from mitigating bias in AI systems to the importance of transparency in models. Monitoring and maintaining ML systems performance is also covered in detail, along with regulatory compliance and risk management considerations. Moreover, the book explores strategies for fostering a data-driven culture within organizations and offers guidance on change management to ensure successful adoption of data governance initiatives. Looking ahead, the book examines future trends and emerging challenges in ML data governance, such as Explainable AI (XAI) and the increasing complexity of data. What You Will Learn Comprehensive understanding of machine learning and data governance, including fundamental principles, critical practices, and emerging challenges Navigating the complexities of managing data effectively within the context of machine learning projects Practical strategies and best practices for implementing effective data governance in machine learning projects Key aspects such as data quality, privacy, security, and ethical considerations, ensuring responsible and effective use of data Preparation for the evolving landscape of ML data governance with a focus on future trends and emerging challenges in the rapidly evolving field of AI and machine learning Who This Book Is For Data professionals, including data scientists, data engineers, AI developers, or data governance specialists, as well as managers or decision makers looking to implement or improve data governance practices for machine learning projects
Introduction To Data Governance For Machine Learning Systems
DOWNLOAD
Author : Aditya Nandan Prasad
language : en
Publisher: Apress
Release Date : 2024-12-28
Introduction To Data Governance For Machine Learning Systems written by Aditya Nandan Prasad and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-28 with Computers categories.
This book is the first comprehensive guide to the intersection of data governance and machine learning (ML) projects. As ML applications proliferate, the quality, reliability, and ethical use of data is central to their success, which gives ML data governance unprecedented significance. However, adapting data governance principles to ML systems presents unique, complex challenges. Author Aditya Nandan Prasad equips you with the knowledge and tools needed to navigate this dynamic landscape effectively. Through this guide, you will learn to implement robust and responsible data governance practices, ensuring the development of sustainable, ethical, and future-proofed AI applications. The book begins by covering fundamental principles and practices of underlying ML applications and data governance before diving into the unique challenges and opportunities at play when adapting data governance theory and practice to ML projects, including establishing governance frameworks, ensuring data quality and interpretability, preprocessing, and the ethical implications of ML algorithms and techniques, from mitigating bias in AI systems to the importance of transparency in models. Monitoring and maintaining ML systems performance is also covered in detail, along with regulatory compliance and risk management considerations. Moreover, the book explores strategies for fostering a data-driven culture within organizations and offers guidance on change management to ensure successful adoption of data governance initiatives. Looking ahead, the book examines future trends and emerging challenges in ML data governance, such as Explainable AI (XAI) and the increasing complexity of data. What You Will Learn Comprehensive understanding of machine learning and data governance, including fundamental principles, critical practices, and emerging challenges Navigating the complexities of managing data effectively within the context of machine learning projects Practical strategies and best practices for implementing effective data governance in machine learning projects Key aspects such as data quality, privacy, security, and ethical considerations, ensuring responsible and effective use of data Preparation for the evolving landscape of ML data governance with a focus on future trends and emerging challenges in the rapidly evolving field of AI and machine learning Who This Book Is For Data professionals, including data scientists, data engineers, AI developers, or data governance specialists, as well as managers or decision makers looking to implement or improve data governance practices for machine learning projects
Data Governance Devsecops And Advancements In Modern Software
DOWNLOAD
Author : Elbaghazaoui, Bahaa Eddine
language : en
Publisher: IGI Global
Release Date : 2025-04-24
Data Governance Devsecops And Advancements In Modern Software written by Elbaghazaoui, Bahaa Eddine and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-24 with Computers categories.
In today’s digital landscape, data governance, DevSecOps, and advancements in modern software development have become critical in secure and efficient technology ecosystems. As organizations rely on large amounts of data and sophisticated software systems to drive innovation and business success, the need for improved frameworks to manage, protect, and optimize this data increases. Data governance ensures data is accurate, secure, and compliant with regulations, while DevSecOps, an integrated approach to development, security, and operations, empowers teams to build, test, and utilize software with security embedded through its lifecycle. Along with the latest advancements in modern software technologies, these concepts form the foundation for building resilient, secure, and scalable applications. The intersection of these practices shapes the future of how software is developed, deployed, and governed, and further research may provide both opportunities and challenges for connection. Data Governance, DevSecOps, and Advancements in Modern Software explores the integration of key technologies and methodologies that define the modern digital landscape, with a focus on DataOps, DevSecOps, data governance, and software architecture. It provides a comprehensive guide to managing data workflows and enhancing operational efficiency while embedding security at every stage of the development lifecycle. This book covers topics such as data science, artificial intelligence, and resilient systems, and is a useful resource for data scientists, engineers, software developers, business owners, researchers, and academicians.
Modeling And Profiling Taxpayer Behavior And Compliance
DOWNLOAD
Author : Alj, Bouchra
language : en
Publisher: IGI Global
Release Date : 2025-04-23
Modeling And Profiling Taxpayer Behavior And Compliance written by Alj, Bouchra and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-23 with Business & Economics categories.
In a society where there is mounting pressure on public finances, exacerbated by recurring economic crises, the issue of tax compliance becomes a significant topic of discussion in the academic, political, and social spheres. It plays a pivotal role in ensuring fiscal stability, social justice, and economic stability. However, governments around the world face an increasing prevalence of tax evasion, more sophisticated tax optimization practices, the complexity of tax regimes and a growing distrust of institutions by citizens. These challenges test the capacity of governments to ensure a stable and fair tax base. Modeling and Profiling Taxpayer Behavior and Compliance explores the major challenges of tax compliance through the lens of taxpayer behavior, shaped by a multitude of economic, psychological, sociological, cultural, institutional, legal, political, and technological factors. It examines the factors that influence the way individuals and companies comply with their tax obligations. Covering topics such as tax morality, communication strategies, and creative accounting, this book is an excellent resource for tax inspectors, lawyers, and advisors, auditors, accountants, policymakers, legislators, business leaders, entrepreneurs, researchers, academicians, and more.
The Enterprise Big Data Lake
DOWNLOAD
Author : Alex Gorelik
language : en
Publisher: O'Reilly Media
Release Date : 2019-02-21
The Enterprise Big Data Lake written by Alex Gorelik and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-21 with Computers categories.
The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises. You’ll learn what a data lake is, why enterprises need one, and how to build one successfully with the best practices in this book. Alex Gorelik, CTO and founder of Waterline Data, explains why old systems and processes can no longer support data needs in the enterprise. Then, in a collection of essays about data lake implementation, you’ll examine data lake initiatives, analytic projects, experiences, and best practices from data experts working in various industries. Get a succinct introduction to data warehousing, big data, and data science Learn various paths enterprises take to build a data lake Explore how to build a self-service model and best practices for providing analysts access to the data Use different methods for architecting your data lake Discover ways to implement a data lake from experts in different industries
Information Systems
DOWNLOAD
Author : Marinos Themistocleous
language : en
Publisher: Springer
Release Date : 2019-01-11
Information Systems written by Marinos Themistocleous and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-11 with Computers categories.
This book constitutes selected papers from the 15th European, Mediterranean, and Middle Eastern Conference, EMCIS 2018, held in Limassol, Cyprus, in October 2018. EMCIS is dedicated to the definition and establishment of Information Systems as a discipline of high impact for the methodical community and IS professionals, focusing on approaches that facilitate the identification of innovative research of significant relevance to the IS discipline. The 34 full and 8 short papers presented in this volume were carefully reviewed and selected from a total of 108 submissions. They were organized in topical sections named: blockchain technology and applications; big data and analytics; cloud computing; digital services and social media; e-government; healthcare information systems; IT governance; and management and organizational issues in information systems.
Data Governance
DOWNLOAD
Author : Dimitrios Sargiotis
language : en
Publisher: Springer Nature
Release Date : 2024-09-11
Data Governance written by Dimitrios Sargiotis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-11 with Computers categories.
This book is a comprehensive resource designed to demystify the complex world of data governance for professionals across various sectors. This guide provides in-depth insights, methodologies, and best practices to help organizations manage their data effectively and securely. It covers essential topics such as data quality, privacy, security, and management ensuring that readers gain a holistic understanding of how to establish and maintain a robust data governance framework. Through a blend of theoretical knowledge and practical applications, this book addresses the challenges and benefits of data governance, equipping readers with the tools needed to navigate the evolving data landscape. In addition to foundational principles, this book explores real-world case studies that illustrate the tangible benefits and common pitfalls of implementing data governance. Emerging trends and technologies, including artificial intelligence, machine learning, and blockchain are also examined to prepare readers for future developments in the field. Whether you are a seasoned data management professional or new to the discipline, this book serves as an invaluable resource for mastering the intricacies of data governance and leveraging data as a strategic asset for organizational success. This resourceful guide targets data management professionals, IT managers, Compliance officers, Data Stewards, Data Owners Data Governance Managers and more. Business leaders, business executives academic researchers, students focused on computer science in data-related fields will also find this book a useful resource.
Policy Based Autonomic Data Governance
DOWNLOAD
Author : Seraphin Calo
language : en
Publisher: Springer
Release Date : 2019-04-24
Policy Based Autonomic Data Governance written by Seraphin Calo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-24 with Computers categories.
Advances in artificial intelligence, sensor computing, robotics, and mobile systems are making autonomous systems a reality. At the same time, the influence of edge computing is leading to more distributed architectures incorporating more autonomous elements. The flow of information is critical in such environments, but the real time, distributed nature of the system components complicates the data protection mechanisms. Policy-based management has proven useful in simplifying the complexity of management in domains like networking, security, and storage; it is expected that many of those benefits would carry over to the task of managing big data and autonomous systems. This book aims at providing an overview of recent work and identifying challenges related to the design of policy-based approaches for managing big data and autonomous systems. An important new direction explored in the book is to make the major elements of the system self-describing and self-managing. This would lead to architectures where policy mechanisms are tightly coupled with the system elements. In such integrated architectures, we need new models for information assurance, traceability of information, and better provenance on information flows. In addition when dealing with devices with actuation capabilities and, thus, being able to make changes to physical spaces, safety is critical. With an emphasis on policy-based mechanisms for governance of data security and privacy, and for safety assurance, the papers in this volume follow three broad themes: foundational principles and use-cases for the autonomous generation of policies; safe autonomy; policies and autonomy in federated environments.
Developments Towards Next Generation Intelligent Systems For Sustainable Development
DOWNLOAD
Author : Sharma, Shanu
language : en
Publisher: IGI Global
Release Date : 2024-04-04
Developments Towards Next Generation Intelligent Systems For Sustainable Development written by Sharma, Shanu and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-04 with Business & Economics categories.
The rapid proliferation of connected devices in our daily lives, from smart homes to industrial sensors, has led to an explosion of data that requires processing before it is useful to experts. However, modern devices often have limited resources, making it challenging to decode and utilize this data effectively. Additionally, the need for real-time decision-making further complicates this issue, as traditional data processing methods take far too long to be able to keep up with the required volume and speed. Developments Towards Next Generation Intelligent Systems for Sustainable Development offers a comprehensive solution to these challenges by integrating novel technologies such as AI, edge computing, federated learning, quantum computing, and more. The book shows how intelligent systems can maximize computing power by leveraging these technologies to process large volumes of data efficiently and autonomously and make real-time decisions. The proposed architectures and frameworks focus on real-time analysis, faster decision-making, enhanced privacy, and efficient data processing.
Advances In Service Oriented And Cloud Computing
DOWNLOAD
Author : Christian Zirpins
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Advances In Service Oriented And Cloud Computing written by Christian Zirpins and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Computers categories.
This volume contains the technical papers presented in the workshops, which took place at the 9th European Conference on Service-Oriented and Cloud Computing, ESOCC 2022, held in Wittenberg, Germany, in March 2022. The 4 full papers and 7 short papers included in these proceedings were carefully reviewed and selected from 17 submissions. The workshop proceedings volume of ESOCC 2022 contains contributions from the following workshops and events: First International Workshop on AI for Web Application Infrastructure and Cloud Platform Security (AWACS 2022)PhD Symposium of ESOCC 2022ESOCC 2022 Projects TrackESOCC 2022 Industrial Track