Theory And Practice Of Quality Assurance For Machine Learning Systems
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Theory And Practice Of Quality Assurance For Machine Learning Systems
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Author : Samuel Ackerman
language : en
Publisher: Springer Nature
Release Date : 2024-10-26
Theory And Practice Of Quality Assurance For Machine Learning Systems written by Samuel Ackerman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-26 with Computers categories.
This book is a self-contained introduction to engineering and testing machine learning (ML) systems. It systematically discusses and teaches the art of crafting and developing software systems that include and surround machine learning models. Crafting ML based systems that are business-grade is highly challenging, as it requires statistical control throughout the complete system development life cycle. To this end, the book introduces an “experiment first” approach, stressing the need to define statistical experiments from the beginning of the development life cycle and presenting methods for careful quantification of business requirements and identification of key factors that impact business requirements. Applying these methods reduces the risk of failure of an ML development project and of the resultant, deployed ML system. The presentation is complemented by numerous best practices, case studies and practical as well as theoretical exercises and their solutions, designed to facilitate understanding of the ideas, concepts and methods introduced. The goal of this book is to empower scientists, engineers, and software developers with the knowledge and skills necessary to create robust and reliable ML software.
Theory And Practice Of Quality Assurance For Machine Learning Systems
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Author : Samuel Ackerman
language : en
Publisher: Springer
Release Date : 2024-10-24
Theory And Practice Of Quality Assurance For Machine Learning Systems written by Samuel Ackerman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-24 with Computers categories.
This book is a self-contained introduction to engineering and testing machine learning (ML) systems. It systematically discusses and teaches the art of crafting and developing software systems that include and surround machine learning models. Crafting ML based systems that are business-grade is highly challenging, as it requires statistical control throughout the complete system development life cycle. To this end, the book introduces an “experiment first” approach, stressing the need to define statistical experiments from the beginning of the development life cycle and presenting methods for careful quantification of business requirements and identification of key factors that impact business requirements. Applying these methods reduces the risk of failure of an ML development project and of the resultant, deployed ML system. The presentation is complemented by numerous best practices, case studies and practical as well as theoretical exercises and their solutions, designed to facilitate understanding of the ideas, concepts and methods introduced. The goal of this book is to empower scientists, engineers, and software developers with the knowledge and skills necessary to create robust and reliable ML software.
Software Testing And Quality Assurance
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Author : Kshirasagar Naik
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-23
Software Testing And Quality Assurance written by Kshirasagar Naik and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-23 with Computers categories.
A superior primer on software testing and quality assurance, from integration to execution and automation This important new work fills the pressing need for a user-friendly text that aims to provide software engineers, software quality professionals, software developers, and students with the fundamental developments in testing theory and common testing practices. Software Testing and Quality Assurance: Theory and Practice equips readers with a solid understanding of: Practices that support the production of quality software Software testing techniques Life-cycle models for requirements, defects, test cases, and test results Process models for units, integration, system, and acceptance testing How to build test teams, including recruiting and retaining test engineers Quality Models, Capability Maturity Model, Testing Maturity Model, and Test Process Improvement Model Expertly balancing theory with practice, and complemented with an abundance of pedagogical tools, including test questions, examples, teaching suggestions, and chapter summaries, this book is a valuable, self-contained tool for professionals and an ideal introductory text for courses in software testing, quality assurance, and software engineering.
Machine Learning For Software Quality And Reliability Transforming Software Engineering
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Author : Hariprasad Sivaraman
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2020-11-13
Machine Learning For Software Quality And Reliability Transforming Software Engineering written by Hariprasad Sivaraman and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-13 with Computers categories.
As software systems grow in complexity, ensuring quality, reliability, and efficiency has become more challenging than ever. Machine Learning for Software Quality and Reliability explores how AI-driven techniques are revolutionizing software engineering, enhancing defect prediction, automating testing, and optimizing performance. This book provides a deep dive into machine learning applications across the software development lifecycle. Readers will discover how ML models improve defect detection, automate test case generation, and enhance predictive maintenance, reducing downtime and increasing system stability. Key topics include supervised and unsupervised learning for software quality, anomaly detection for reliability engineering, and ML- powered root cause analysis. By integrating real-world case studies from leading technology companies, the book demonstrates how AI- driven quality assurance improves efficiency and scalability across industries. Learn how Google, Microsoft, and Netflix leverage ML to enhance software reliability, minimize bugs, and optimize continuous integration/continuous deployment (CI/CD) pipelines. With a focus on practical implementation, Machine Learning for Software Quality and Reliability equips software engineers, IT leaders, and quality assurance professionals with actionable insights to integrate ML into their workflows. Whether you ' re seeking to automate testing, enhance system resilience, or improve software reliability, this book provides the roadmap to harnessing AI for the next generation of high-quality software development.
Fundamental Approaches To Software Engineering
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Author : Leen Lambers
language : en
Publisher: Springer Nature
Release Date : 2023-04-19
Fundamental Approaches To Software Engineering written by Leen Lambers and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-19 with Computers categories.
This open access book constitutes the proceedings of the 26th International Conference on Fundamental Approaches to Software Engineering, FASE 2023, which was held during April 22-27, 2023, in Paris, France, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2023. The 12 regular papers presented in this volume were carefully reviewed and selected from 50 submissions. The proceedings also contain 2 tool papers, 2 NIER papers, and 2 competition papers from the Test-Comp Competition. The papers deal with the foundations on which software engineering is built, including topics like software engineering as an engineering discipline, requirements engineering, software architectures, software quality, model-driven development, software processes, software evolution, AI-based software engineering, and the specification, design, and implementation of particular classes of systems, such as (self-)adaptive, collaborative, AI, embedded, distributed, mobile, pervasive, cyber-physical, or service-oriented applications. .
Datalog Reloaded
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Author : Oege de Moor
language : en
Publisher: Springer
Release Date : 2012-01-28
Datalog Reloaded written by Oege de Moor and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-28 with Computers categories.
This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Datalog 2.0, held in Oxford, UK, in March 2010. The 22 revised full papers presented were carefully selected during two rounds of reviewing and improvements from numerous submissions. The papers showcase the state-of-the-art in theory and systems for datalog, divided in three sections: Properties, applications, and extensions of datalog.
Data Science In Theory And Practice
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Author : Maria Cristina Mariani
language : en
Publisher: John Wiley & Sons
Release Date : 2021-10-12
Data Science In Theory And Practice written by Maria Cristina Mariani and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with Mathematics categories.
DATA SCIENCE IN THEORY AND PRACTICE EXPLORE THE FOUNDATIONS OF DATA SCIENCE WITH THIS INSIGHTFUL NEW RESOURCE Data Science in Theory and Practice delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. The book offers readers a multitude of topics all relevant to the analysis of complex data sets. Along with a robust exploration of the theory underpinning data science, it contains numerous applications to specific and practical problems. The book also provides examples of code algorithms in R and Python and provides pseudo-algorithms to port the code to any other language. Ideal for students and practitioners without a strong background in data science, readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets Perfect for advanced undergraduate and graduate students in Data Science, Business Analytics, and Statistics programs, Data Science in Theory and Practice will also earn a place in the libraries of practicing data scientists, data and business analysts, and statisticians in the private sector, government, and academia.
A Decade Of Moocs And Beyond
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Author : Irwin King
language : en
Publisher: Springer Nature
Release Date : 2022-12-14
A Decade Of Moocs And Beyond written by Irwin King and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-14 with Education categories.
This book is an academic publication about the global development of massive open online courses (MOOCs) and major MOOC platforms worldwide in the past decade, as well as the outlook of MOOCs in the future, with an emphasis on Greater China. The book also discusses the upsurge of the demand for online learning and MOOCs during the COVID-19 pandemic. The book is divided into three main parts - Part I: Overview of MOOCs introduces the origin and history of MOOCs and the development of MOOC platforms in Greater China and the global context; Part II: Key Issues discuss the MOOC policies, innovative pedagogy, technology, and ecosystems worldwide; and Part III: Beyond MOOCs probes into the roles and benefits of MOOCs in times of crises, as well as the outlook of MOOCs in the future. In terms of topic diversity, the book contains a comprehensive investigation of the past and latest MOOC developments, extracting and elaborating on relevant information regarding platforms, policies, pedagogy, technology, and ecosystems. Subsequently, in-depth analyses of MOOC data are utilized to deduce the current trends related to the MOOC movement and to extrapolate the likeliest direction of development for MOOCs in the years to come. The book can inform policymakers, education institutions, course instructors, platform developers, investors, researchers, and individual learners of MOOCs about critical information on the present and future of MOOC development, assisting them in making crucial decisions on what initiatives can optimize their advantages in the sector.
Web 3 0
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Author : Prabhat Kumar Srivastav
language : en
Publisher: CRC Press
Release Date : 2024-08-01
Web 3 0 written by Prabhat Kumar Srivastav and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-01 with Computers categories.
The book underscores AI's transformative impact on reshaping physical, digital, and biological boundaries, converging with technologies like robotics, IoT, 3D printing, genetic engineering, and quantum computing—termed Web 3.0 Industrial Revolution. This global revolution integrates advanced production techniques beyond connected machines, extending into gene sequencing, nanotechnology, renewable energies, and quantum computing. The book's main goals include providing a collaborative platform for academia and industry researchers to share contributions and shape the future through knowledge exchange. Recognizing recent progress driven by increased computing power, it highlights the positive impact of digital technology—AI, IoT, AR/VR, Additive Manufacturing, CPS, cloud computing, and robotics—on industrial efficiency and quality. Revolutionary AI Fusion: AI revolutionizes by blending physical, digital, and biological boundaries through cutting-edge technologies like robotics, IoT, 3D printing, genetic engineering, and quantum computing. Global Manufacturing Cooperation: AI creates a collaborative landscape where virtual and physical systems flexibly cooperate on a global scale. AI's Diverse Impact: Beyond smart machines, AI drives breakthroughs in gene sequencing, nanotechnology, renewable energies, and quantum computing, distinguishing it from prior industrial revolutions. Progress and Digital Interface: Recent progress, powered by computing advancements, boosts industrial efficiency. The digital technology interface (AI, IoT, AR/VR, 3D Printing, CPS, CC, Robotics) significantly impacts industrial performance. In conclusion, AI spearheads a transformative revolution, redefining the boundaries of the physical, digital, and biological realms. The fusion of AI with Web 3.0 Industrial Revolution, integrating advanced production techniques and global manufacturing cooperation, surpassing past industrial shifts. The book aims to be a collaborative platform for academia and industry researchers, fostering knowledge exchange to shape the future. In AI-driven manufacturing within Web 3.0, a paradigm shift envisions maximum output with minimal resource use. Coupled with 'Digital Reality,' it transforms business practices, consumer behaviour, and employment dynamics, redistributing wealth toward innovation and technology.
Software Testing And Quality Assurance
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Author : Kshirasagar Naik
language : en
Publisher: Wiley
Release Date : 2017-01-04
Software Testing And Quality Assurance written by Kshirasagar Naik and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-04 with Computers categories.
This book introduces the fundamental ideas in testing theory, testing techniques, testing practices and quality assurance. Software Testing and Quality Assurance: Theory and Practice covers the practices that support the production of quality software, software testing techniques, life-cycle models for requirements, defects, test cases, test results, test questions, examples, teaching suggestions, and chapter summaries. Other topics covered are; software quality assurance (SQA), SQA processes and metrics; the role of testing; basics of program testing; theory of program testing; code review; unit testing; test generation from control flow graphs, data flow graphs, and program domains; system integration; system testing; test execution; test automation; acceptance testing; quality metrics and reliability models. For the 2nd edition, the authors have included two major topics: (i) Boolean expression testing; and (ii) testing without oracles.