Homepage / Searching for: data science in engineering and management

Welcome to Read Book Online

Download data science in engineering and management or read data science in engineering and management online books in PDF, EPUB and Mobi Format. Click Download or Read Online button to get data science in engineering and management book now. Note:! If the content not Found, you must refresh this page manually.

Data Science In Engineering And Management

DOWNLOAD
Author by : Zdzislaw Polkowski
Languange Used : en
Release Date : 2021-12-30
Publisher by : CRC Press

ISBN : 9781000520774

This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines....

Enterprise Big Data Engineering Analytics And Management

DOWNLOAD
Author by : Atzmueller, Martin
Languange Used : en
Release Date : 2016-06-01
Publisher by : IGI Global

ISBN : 9781522502944

The significance of big data can be observed in any decision-making process as it is often used for forecasting and predictive analytics. Additionally, big data can be used to build a holistic view of an enterprise through a collection and analysis of large data sets retrospectively. As the data deluge deepens, new methods for analyzing, comprehending, and making use of big data become necessary. Enterprise Big Data Engineering, Analytics, and Management presents novel methodologies and practical approaches to engineering, managing, and analyzing large-scale data sets with a focus on enterprise applications and implementation. Featuring essential big data concepts including data mining, artificial intelligence, and information extraction, this publication provides a platform for retargeting the current research available in the field. Data analysts, IT professionals, researchers, and graduate-level students will find the timely research presented in this publication essential to furthering their knowledge in the field....

Data Analytics For Engineering And Construction Project Risk Management

DOWNLOAD
Author by : Ivan Damnjanovic
Languange Used : en
Release Date : 2019-05-23
Publisher by : Springer

ISBN : 9783030142513

This book provides a step-by-step guidance on how to implement analytical methods in project risk management. The text focuses on engineering design and construction projects and as such is suitable for graduate students in engineering, construction, or project management, as well as practitioners aiming to develop, improve, and/or simplify corporate project management processes. The book places emphasis on building data-driven models for additive-incremental risks, where data can be collected on project sites, assembled from queries of corporate databases, and/or generated using procedures for eliciting experts’ judgments. While the presented models are mathematically inspired, they are nothing beyond what an engineering graduate is expected to know: some algebra, a little calculus, a little statistics, and, especially, undergraduate-level understanding of the probability theory. The book is organized in three parts and fourteen chapters. In Part I the authors provide the general introduction to risk and uncertainty analysis applied to engineering construction projects. The basic formulations and the methods for risk assessment used during project planning phase are discussed in Part II, while in Part III the authors present the methods for monitoring and (re)assessment of risks during project execution....

Managing Data Science

DOWNLOAD
Author by : Kirill Dubovikov
Languange Used : en
Release Date : 2019-11-12
Publisher by : Packt Publishing Ltd

ISBN : 9781838824563

Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organization Key FeaturesLearn the basics of data science and explore its possibilities and limitationsManage data science projects and assemble teams effectively even in the most challenging situationsUnderstand management principles and approaches for data science projects to streamline the innovation processBook Description Data science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don't entirely meet the conditions and requirements necessary for current data science projects. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps. By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you'll encounter on a daily basis. What you will learnUnderstand the underlying problems of building a strong data science pipelineExplore the different tools for building and deploying data science solutionsHire, grow, and sustain a data science teamManage data science projects through all stages, from prototype to productionLearn how to use ModelOps to improve your data science pipelinesGet up to speed with the model testing techniques used in both development and production stagesWho this book is for This book is for data scientists, analysts, and program managers who want to use data science for business productivity by incorporating data science workflows efficiently. Some understanding of basic data science concepts will be useful to get the most out of this book....

Advances In Data Science And Information Engineering

DOWNLOAD
Author by : Robert Stahlbock
Languange Used : en
Release Date : 2021-10-29
Publisher by : Springer Nature

ISBN : 9783030717049

The book presents the proceedings of two conferences: the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020), which took place in Las Vegas, NV, USA, July 27-30, 2020. The conferences are part of the larger 2020 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE'20), which features 20 major tracks. Papers cover all aspects of Data Science, Data Mining, Machine Learning, Artificial and Computational Intelligence (ICDATA) and Information Retrieval Systems, Information & Knowledge Engineering, Management and Cyber-Learning (IKE). Authors include academics, researchers, professionals, and students. Presents the proceedings of the 16th International Conference on Data Science (ICDATA 2020) and the 19th International Conference on Information & Knowledge Engineering (IKE 2020); Includes papers on topics from data mining to machine learning to informational retrieval systems; Authors include academics, researchers, professionals and students....

Data Science For Undergraduates

DOWNLOAD
Author by : National Academies of Sciences, Engineering, and Medicine
Languange Used : en
Release Date : 2018-10-11
Publisher by : National Academies Press

ISBN : 9780309475624

Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field....

Analytics And Tech Mining For Engineering Managers

DOWNLOAD
Author by : Scott W. Cunningham
Languange Used : en
Release Date : 2016-06-20
Publisher by : Momentum Press

ISBN : 9781606505113

This book offers practical tools in Python to students of innovation, as well as competitive intelligence professionals, to track new developments in science, technology, and innovation. The book will appeal to both—tech-mining and data science audiences. For tech-mining audiences, Python presents an appealing, all-in-one language for managing the tech-mining process. The book is a complement to other introductory books on the Python language, providing recipes with which a practitioner can grow a practice of mining text. For data science audiences, this book gives a succinct overview over the most useful techniques of text mining. The book also provides relevant domain knowledge from engineering management; so, an appropriate context for analysis can be created. This is the first book of a two-book series. This first book discusses the mining of text, while the second one describes the analysis of text. This book describes how to extract actionable intelligence from a variety of sources including scientific articles, patents, pdfs, and web pages. There is a variety of tools available within Python for mining text. In particular, we discuss the use of pandas, BeautifulSoup, and pdfminer....

Iot And Data Science In Engineering Management

DOWNLOAD
Author by : Fausto Pedro García Márquez
Languange Used : en
Release Date : 2023-03-24
Publisher by : Springer Nature

ISBN : 9783031279157

This book presents the selected research works from the 16th International Conference on Industrial Engineering and Industrial Management in 2022. The conference was promoted by ADINGOR (Asociación para el Desarrollo de la Ingeniería de Organización), organized by Ingenium Research Group at Universidad de Castilla-La Mancha, Spain, and it took place on July 7th and 8th, 2022, in Toledo, Spain. The book highlights some of the latest research advances and cutting-edge analyses of real-world case studies on Industrial Engineering and Industrial Management from a wide range of international contexts. It also identifies business applications and the latest findings and innovations in Operations Management and in Decision Sciences....

Strengthening Data Science Methods For Department Of Defense Personnel And Readiness Missions

DOWNLOAD
Author by : National Academies of Sciences, Engineering, and Medicine
Languange Used : en
Release Date : 2017-02-06
Publisher by : National Academies Press

ISBN : 9780309450812

The Office of the Under Secretary of Defense (Personnel & Readiness), referred to throughout this report as P&R, is responsible for the total force management of all Department of Defense (DoD) components including the recruitment, readiness, and retention of personnel. Its work and policies are supported by a number of organizations both within DoD, including the Defense Manpower Data Center (DMDC), and externally, including the federally funded research and development centers (FFRDCs) that work for DoD. P&R must be able to answer questions for the Secretary of Defense such as how to recruit people with an aptitude for and interest in various specialties and along particular career tracks and how to assess on an ongoing basis service members' career satisfaction and their ability to meet new challenges. P&R must also address larger-scale questions, such as how the current realignment of forces to the Asia-Pacific area and other regions will affect recruitment, readiness, and retention. While DoD makes use of large-scale data and mathematical analysis in intelligence, surveillance, reconnaissance, and elsewhereâ€"exploiting techniques such as complex network analysis, machine learning, streaming social media analysis, and anomaly detectionâ€"these skills and capabilities have not been applied as well to the personnel and readiness enterprise. Strengthening Data Science Methods for Department of Defense Personnel and Readiness Missions offers and roadmap and implementation plan for the integration of data analysis in support of decisions within the purview of P&R....

Perspectives On Data Science For Software Engineering

DOWNLOAD
Author by : Tim Menzies
Languange Used : en
Release Date : 2016-07-14
Publisher by : Morgan Kaufmann

ISBN : 9780128042618

Perspectives on Data Science for Software Engineering presents the best practices of seasoned data miners in software engineering. The idea for this book was created during the 2014 conference at Dagstuhl, an invitation-only gathering of leading computer scientists who meet to identify and discuss cutting-edge informatics topics. At the 2014 conference, the concept of how to transfer the knowledge of experts from seasoned software engineers and data scientists to newcomers in the field highlighted many discussions. While there are many books covering data mining and software engineering basics, they present only the fundamentals and lack the perspective that comes from real-world experience. This book offers unique insights into the wisdom of the community’s leaders gathered to share hard-won lessons from the trenches. Ideas are presented in digestible chapters designed to be applicable across many domains. Topics included cover data collection, data sharing, data mining, and how to utilize these techniques in successful software projects. Newcomers to software engineering data science will learn the tips and tricks of the trade, while more experienced data scientists will benefit from war stories that show what traps to avoid. Presents the wisdom of community experts, derived from a summit on software analytics Provides contributed chapters that share discrete ideas and technique from the trenches Covers top areas of concern, including mining security and social data, data visualization, and cloud-based data Presented in clear chapters designed to be applicable across many domains...