Описание: Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately.
Автор: Siegel Eric Название: Predictive Analytics ISBN: 1118356853 ISBN-13(EAN): 9781118356852 Издательство: Wiley Рейтинг: Цена: 3259 р. Наличие на складе: Поставка под заказ.
"The "Freakonomics" of big data." --Stein Kretsinger, founding executive of Advertising.com
Award-winning - Used by over 30 universities - Translated into 9 languages
"An introduction for everyone. ""In this rich, fascinating -- surprisingly accessible -- introduction, leading expert Eric Siegel reveals how predictive analytics works, and how it affects everyone every day. Rather than a "how to" for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques."
Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing "unnatural" resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise This heap of refuse is a gold mine. "Big data" embodies an extraordinary wealth of experience from which to learn." Predictive Analytics" unleashes the power of data. With this technology," " the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction -- "now in its Revised and Updated edition" -- former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death -- including one health insurance company. How U.S. Bank and Obama for America calculated -- and Hillary for America 2016 plans to calculate -- the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used "predictive modeling" to answer questions and beat the human champs on TV's "Jeopardy " How companies ascertain untold, private truths -- how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 183 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more.
How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more.""
A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a consumer of it -- or consumed by it -- get a handle on the power of "Predictive Analytics."
Автор: Jac Fitz?€“enz,John Mattox II Название: Predictive Analytics for Human Resources ISBN: 1118893670 ISBN-13(EAN): 9781118893678 Издательство: Wiley Рейтинг: Цена: 6692 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Create and run a human resource analytics project with confidence For any human resource professional that wants to harness the power of analytics, this essential resource answers the questions: "Where do I start?" and "What tools are available?" Predictive Analytics for Human Resources is designed to answer these and other vital questions.
Описание: Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution.
Автор: Larose Daniel T Название: Data Mining and Predictive Analytics ISBN: 1118116194 ISBN-13(EAN): 9781118116197 Издательство: Wiley Рейтинг: Цена: 20412 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis.
Автор: Finlay Steven Название: Predictive Analytics, Data Mining and Big Data ISBN: 1137379278 ISBN-13(EAN): 9781137379276 Издательство: Springer Рейтинг: Цена: 6121 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.
Автор: Colleen McCue Название: Data Mining and Predictive Analysis ISBN: 0128002298 ISBN-13(EAN): 9780128002292 Издательство: Elsevier Science Рейтинг: Цена: 10764 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive,security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining inhomeland security, security analysis, and operational law enforcementsettings.This revised text highlights new and emerging technology, discusses the importance of analytic contextfor ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models that increase ease of use and access to high-end technology and analytic capabilities. The use of predictive analytics inintelligence and securityanalysis enables the development of meaningful, information based tactics, strategy, and policy decisions in the operational public safety and security environment.
Автор: Tayebi Название: Social Network Analysis in Predictive Policing ISBN: 3319414917 ISBN-13(EAN): 9783319414911 Издательство: Springer Рейтинг: Цена: 11784 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book focuses on applications of social network analysis in predictive policing. Data science is used to identify potential criminal activity by analyzing the relationships between offenders to fully understand criminal collaboration patterns. Co-offending networks—networks of offenders who have committed crimes together—have long been recognized by law enforcement and intelligence agencies as a major factor in the design of crime prevention and intervention strategies. Despite the importance of co-offending network analysis for public safety, computational methods for analyzing large-scale criminal networks are rather premature. This book extensively and systematically studies co-offending network analysis as effective tool for predictive policing. The formal representation of criminological concepts presented here allow computer scientists to think about algorithmic and computational solutions to problems long discussed in the criminology literature. For each of the studied problems, we start with well-founded concepts and theories in criminology, then propose a computational method and finally provide a thorough experimental evaluation, along with a discussion of the results. In this way, the reader will be able to study the complete process of solving real-world multidisciplinary problems.
Автор: Prof. Dr. Florian von Wangenheim; Markus W?bben Название: Analytical CRM ISBN: 3834912786 ISBN-13(EAN): 9783834912787 Издательство: Springer Рейтинг: Цена: 13774 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The ever-increasing amount of individual-level customer data generated by reward/l- alty programs opens new perspectives for customer relationship management (CRM). Without any question, the potential bene?ts of these data and analytical models for - plaining, extending, and predicting customer behavior is very high. However, recent analyses have shown that a high fraction of CRM projects result in negative return on investment. One of the main reasons for this dilemma is that these data require advanced analytical processing to fully leverage their potential ("analytical CRM"). Yet, research and practice is still in its early stages with respect to analytical CRM. In particular, the so-called "non-contractual settings" remain widely unexplored. Lit- ature refers to a "non-contractual setting" when customer relationships are not governed by a contract that predetermines the monetary value and/or length of the relationship. Examples include hotels, airlines, and most retailers. The most obvious consequence for CRM is that the end of a customer relationship is not directly observable, i.e., a c- tomer can switch providers without notifying the focal provider. Consequently, analysis of customer retention, and future buying behavior is even more problematic than in contractual settings.
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