Multidimensional Data Visualization

Data and algorithms are changing our life. The awareness of importance and pervasiveness of the digital revolution is the primary element from which to start a path of knowledge to grasp what is happe

A book about what the Cambridge Analytica scandal shows: That surveillance and data privacy is every citizens’ concernAn important look at how 50 years of American privacy law is inadequate for

A guide that provides in-depth coverage of modeling techniques used throughout many branches of actuarial science, revised and updatedNow in its fifth edition, Loss Models: From Data to Decisions puts the focus on material tested in the Society of Actuaries (SOA) newly revised Exams STAM (Short-Term Actuarial Mathematics) and LTAM (Long-Term Actuarial Mathematics). Updated to reflect these exam changes, this vital resource offers actuaries, and those aspiring to the profession, a practical approach to the concepts and techniques needed to succeed in the profession. The techniques are also valuable for anyone who uses loss data to build models for assessing risks of any kind.Loss Models contains a wealth of examples that highlight the real-world applications of the concepts presented, and puts the emphasis on calculations and spreadsheet implementation. With a focus on the loss process, the book reviews the essential quantitative techniques such as random variables, basic distributional

The first machine-learning guide that helps you understand customers, frame decisions, and drive value Business Data Science reveals the best ways for utilizing machine learning (ML) to mak

Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation su

Data Driven Business Transformation walks you through the journey of how to transform your business to unleash all that hidden value. It makes the business case, taking the reader stage by stage, usin

‘CAA2016: Oceans of Data’ gives an up-to-date overview of the field of archaeology and informatics. It presents ground-breaking technologies and best practice from various archaeological a

Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to

The bestselling guide for school leaders—updated in a new edition Data-driven instruction is the philosophy that schools should focus on two simple questions: how do you know if are student

AN ESSENTIAL GUIDE TO USING BLOCKCHAIN TO PROVIDE FLEXIBILITY, COST-SAVINGS, AND SECURITY TO DATA MANAGEMENT, DATA ANALYSIS, AND INFORMATION SHARINGBlockchain for Distributed Systems Security con

Many industry experts consider unsupervised learning the next AI frontier, one that may hold the key to general artificial intelligence. Armed with the conceptual knowledge in this book, data scientis

Data is fundamental to the modern world. From economic development, to healthcare, to educationand public policy, we rely on numbers to allocate resources and make crucial decisions.But because so muc

Maximize performance with better data Developing a successful workforce requires more than a gut check. Data can help guide your decisions on everything from where to seat a team to optimizing product

This book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes mul

This is the era of Big Data and computational social science. It is an era that requires tools which can do more than visualise data but also model the complex relation between data and huma

This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Manag

This book summarizes five years of learning from data collected as part of the Global Accelerator Learning Initiative. The authors present data describing impact-oriented ventures and accelerators tha

This book introduces the latest research findings in cloud, edge, fog, and mist computing and their applications in various fields using geospatial data. It solves a number of problems of cloud comput

This book discusses the problems of complexity in industrial data, including the problems of data sources, causes and types of data uncertainty, and methods of data preparation for further reasoning i

Providing information from data preparation and mean, median and mode, to regression, Lisa Daniels and Nicholas Minot use concise descriptions to help students understand the concepts behind statistic

Haunted Data explores the contemporary concepts that are at work in our complex relationships with data. And shows how our engagement with data – big or small – is never as simplistic or straightforwa

More than ever, organisations are facing a data avalanche from various sources, be they in electronic or hard copy format. How an organisation manages this ever-increasingly important resource – data

Are you ready to create your own "good charts"--data visualizations that more effectively communicate your ideas and research and that advance your career? The original Good Charts has changed the dat

This book offers data-based insights into the problems of translation education and their causes in the context of localization and globalization in the era of big data. By examining language services

The field of assessing the accuracy of maps derived from remotely sensed data has continued to develop and mature since the first edition of this book in 1999. The third edition will have all chapters

Following the implementation of the new General Data Protect Regulation on 25 May 2018, organizations should now be fully compliant with their national interpretation of this far-reaching data protect

This book is a mathematically accessible and up-to-date introduction to the tools needed to address modern inference problems in engineering and data science, ideal for graduate students taking courses on statistical inference and detection and estimation, and an invaluable reference for researchers and professionals. With a wealth of illustrations and examples to explain the key features of the theory and to connect with real-world applications, additional material to explore more advanced concepts, and numerous end-of-chapter problems to test the reader's knowledge, this textbook is the 'go-to' guide for learning about the core principles of statistical inference and its application in engineering and data science. The password-protected solutions manual and the image gallery from the book are available online.

Paleoecological data from the Quaternary Period (2.6 million years ago to present) provides an opportunity for educational outreach for the earth and biological sciences. Paleoecology data repositories serve as technical hubs and focal points within their disciplinary communities and so are uniquely situated to help produce teaching modules and engagement resources. The Neotoma Paleoecology Database provides support to educators from primary schools to graduate students. In collaboration with pedagogical experts, the Neotoma Paleoecology Database team has developed teaching modules and model workflows. Early education is centered on discovery; higher-level educational tools focus on illustrating best practices for technical tasks. Collaborations among pedagogic experts, technical experts and data stewards, centered around data resources such as Neotoma, provide an important role within research communities, and an important service to society, supporting best practices, translating cur

How do we create new ways of looking at the world? Join award-winning data storyteller RJ Andrews as he pushes beyond the usual how-to, and takes you on an adventure into the rich art of informing.Cre

Despite a long history in quantitative research, it is only recently that enthusiasm for secondary analysis of qualitative data has gained momentum across health and social science disciplines. Given

This straightforward and effective how-to guide provides the basics for any reporter or journalism student beginning to use data for news stories. It has step-by-step instructions on how to do basic d

Rapid advancements in our ability to collect, process, and analyze massive amounts of data along with the widespread use of online and blended learning platforms have enabled educators at all levels t

Big data is marked by staggering growth in the collection and analysis of digital trace information regarding human and natural activity, bound up in and enabled by the rise of persistent connectivity

More than ever organisations are facing a data avalanche from various data sources, be it in electronic or hard copy format. How an organisation manages this ever increasingly important resource - dat

Translational Inflammation links laboratory and clinical data within primary and secondary care to clinical research data and offers a holistic and innovative approach to chronic inflammation and agei

Rapid advancements in our ability to collect, process, and analyze massive amounts of data along with the widespread use of online and blended learning platforms have enabled educators at all levels t

This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation and selection alongside statistical inference. The book covers standard models for categorical data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the authors build an understanding about the contexts in which maximum likelihood methods are useful and develop skills in translating mathematical statements into executable computer code. Readers will not only be taught to use likelihood-based tools and generate meaningful interpretations, but they will also acquire a solid foundation for continued study of more advanced statistical techniques.

Loss Models: From Data to Decisions, Fifth Edition continues to supply actuaries with a practical approach to the key concepts and techniques needed on the job. With updated material and extensive exa

Statistical, Mapping and Digital Approaches in Healthcare addresses all health territories, starting from the analysis of geographical data (health data, population data, health data systems and envir

This volume provides a practical introduction to the method of maximum likelihood as used in social science research. Ward and Ahlquist focus on applied computation in R and use real social science data from actual, published research. Unique among books at this level, it develops simulation-based tools for model evaluation and selection alongside statistical inference. The book covers standard models for categorical data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the authors build an understanding about the contexts in which maximum likelihood methods are useful and develop skills in translating mathematical statements into executable computer code. Readers will not only be taught to use likelihood-based tools and generate meaningful interpretations, but they will also acquire a solid foundation for continued study of more advanced statistical techniques.