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Machine Learning for Business Analytics
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 R 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-life ca...
Infectious Disease Informatics and Biosurveillance
This book on Infectious Disease Informatics (IDI) and biosurveillance is intended to provide an integrated view of the current state of the art, identify technical and policy challenges and opportunities, and promote cross-disciplinary research that takes advantage of novel methodology and what we have learned from innovative applications. This book also fills a systemic gap in the literature by emphasizing informatics driven perspectives (e.g., information system design, data standards, computational aspects of biosurveillance algorithms, and system evaluation). Finally, this book attempts to reach policy makers and practitioners through the clear and effective communication of recent resea...
Machine Learning for Business Analytics
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 R 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-life ca...
Rabbinic Creativity in the Modern Middle East
An exploration of central aspects of Sephardic-Mizrahi rabbinic creativity in the Middle East (Iraq, Syria and Egypt from 1850 to 1950).
Telecommunications Modeling, Policy, and Technology
This book examines the newer and emerging models of telecommunications technology that play instrumental roles in providing international economic and societal interconnectivity. Advancing technology in the field imposes the need to develop new models to solve complex planning and decision making problems. The book explores natural output of the new technical developments and applications with selective chapter treatment on novel business models to fill technical and business needs.
formZ Joint Study Report 2004-05
Material published in this edition is compiled by Dr. Chris Yessios. While no attempt was made to group the articles, since each is quite unique, they can be viewed under a number of thematic categories. There are at least 7 articles that deal more or less directly with the use of digital tools for the generation of innovative forms. Another 8 articles present specific building designs and 5 more present specific urban design schemes. The common denominator for all is the use of the digital tools to create forms that are distinctly different from traditional forms. A group of some 6 papers specifically discusses and compares digital versus analogue methodologies. In all cases, the former are...
On the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE
This two-volume set LNCS 4275/4276 constitutes the refereed proceedings of the four confederated conferences CoopIS 2006, DOA 2006, GADA 2006, and ODBASE 2006 held as OTM 2006 in Montpellier, France in October/November 2006. The 106 revised full and 9 short papers presented together with 4 keynote speeches were carefully reviewed and selected from a total of 361 submissions. Corresponding with the four OTM 2006 main conferences CoopIS, ODBASE, GADA, and DOA, the papers are organized in topical sections on distributed information systems, workflow modelling, workflow management and discovery, dynamic and adaptable workflows, services metrics and pricing, formal approaches to services, trust a...
Practical Statistics for Data Scientists
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap...
97 Things About Ethics Everyone in Data Science Should Know
Most of the high-profile cases of real or perceived unethical activity in data science aren’t matters of bad intent. Rather, they occur because the ethics simply aren’t thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult. In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from collecting, managing, and analyzing data ethically. Data science professionals, managers, and tech leaders will gain a better understanding of ethics through powerful, real-world best practices. Articles include: Ethics Is Not a Binary Conceptâ€...
