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Machine Learning for Business Analytics Machine learning—also known as data mining or data analytics—is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques and Applications in RapidMiner provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation and network analytics. Along with hands-on exercises and real-li...
Annals of Cases on Information Technology provides 37 case studies, authored by over 50 world-renowned academicians and practitioners in information technology each offering insight into how to succeeed in IT projects and how to avoid costly failures. These case studies describe private and public organizations including educational institutions, electronic businesses and governmental organizations ranging in size from small businesses to large organizations. Additionally, they focus on a variety of technology projects including electronic commerce and electronic business initiatives, enterprise resource planning and reengineering efforts, data mining projects and the human factors relating to IT projects.
Technological advances of the past decades have allowed organizations of all sizes to use information technology in all aspects of organizational management. This book presents more than 200 papers that address this growing corporate phenomena.
Businesses are collecting massive amounts of data every day as a way to better understand their processes, competition, and the markets they serve. This data can be used to increase organizational productivity and performance; however, is essential that organizations collecting large data sets have the tools available to them to fully understand the data they are collecting. Organizational Productivity and Performance Measurements Using Predictive Modeling and Analytics takes a critical look at methods for enhancing an organization’s operations and day-to-day activities through the effective use of data. Focusing on a variety of applications of predictive analytics within organizations of all types, this critical publication is an essential resource for business managers, data scientists, graduate-level students, and researchers.
As the world rapidly moves online, sectors from management, industry, government, and education have broadly begun to virtualize the way people interact and learn. Virtual Learning Environments: Concepts, Methodologies, Tools and Applications is a three-volume compendium of the latest research, case studies, theories, and methodologies within the field of virtual learning environments. As networks get faster, cheaper, safer, and more reliable, their applications grow at a rate that makes it difficult for the typical practitioner to keep abreast. With a wide range of subjects, spanning from authors across the globe and with applications at different levels of education and higher learning, this reference guide serves academics and practitioners alike, indexed and categorized easily for study and application.
Technological advances in information technology have created many new ways and structures in our lives. Organizations now are mastering services of this technology in their business strategies, productivity, customer services, and other managerial functions to stay competitive. With a focus on the global issues of IT and its implications on organization, this proceedings includes all the presentations of this international conference.
"This book gives a general coverage of learning management systems followed by a comparative analysis of the particular LMS products, review of technologies supporting different aspect of educational process, and, the best practices and methodologies for LMS-supported course delivery"--Provided by publisher.
As business paradigms shift from desktop-centric environments to data-centric mobile environments, mobile services create numerous new business opportunities. At the same time, these advances may also challenge many of the basic premises of existing business models. Mobile Services Industries, Technologies, and Applications in the Global Economy fosters a scientific understanding of mobile services, provides a timely publication of current research efforts, and forecasts future trends in the mobile services industry and its important role in the world economy. Written for academics, researchers, government policymakers, and corporate managers, this comprehensive volume will outline the great potential for new business models and applications in mobile commerce.
As business paradigm shifts from a desktop-centric environment to a data-centric mobile environment, mobile services provide numerous new business opportunities, and in some cases, challenge some of the basic premises of existing business models. Strategy, Adoption, and Competitive Advantage of Mobile Services in the Global Economy seeks to foster a scientific understanding of mobile services, provide a timely publication of current research efforts, and forecast future trends in the mobile services industry. This book is an ideal resource for academics, researchers, government policymakers, as well as corporate managers looking to enhance their competitive edge in or understanding of mobile services.