applied predictive analytics principles and techniques for the professional data analyst

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Applied Predictive Analytics

Author : Dean Abbott
ISBN : 9781118727690
Genre : Computers
File Size : 78. 37 MB
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Learn the art and science of predictive analytics —techniques that get results Predictive analytics is what translates big data intomeaningful, usable business information. Written by a leadingexpert in the field, this guide examines the science of theunderlying algorithms as well as the principles and best practicesthat govern the art of predictive analytics. It clearly explainsthe theory behind predictive analytics, teaches the methods,principles, and techniques for conducting predictive analyticsprojects, and offers tips and tricks that are essential forsuccessful predictive modeling. Hands-on examples and case studiesare included. The ability to successfully apply predictive analytics enablesbusinesses to effectively interpret big data; essential forcompetition today This guide teaches not only the principles of predictiveanalytics, but also how to apply them to achieve real, pragmaticsolutions Explains methods, principles, and techniques for conductingpredictive analytics projects from start to finish Illustrates each technique with hands-on examples and includesas series of in-depth case studies that apply predictive analyticsto common business scenarios A companion website provides all the data sets used to generatethe examples as well as a free trial version of software Applied Predictive Analytics arms data and businessanalysts and business managers with the tools they need tointerpret and capitalize on big data.

Predictive Analytics

Author : Eric Siegel
ISBN : 9781119153658
Genre : Business & Economics
File Size : 23. 71 MB
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"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "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 (aka machine learning) 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 (aka machine learning) 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 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. 182 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.

Integration Of Data Mining In Business Intelligence Systems

Author : Azevedo, Ana
ISBN : 9781466664784
Genre : Computers
File Size : 66. 56 MB
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Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.

Healthcare S Out Sick Predicting A Cure Solutions That Work

Author : Gary D. Miner
ISBN : 9780429015809
Genre : Medical
File Size : 87. 82 MB
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The U.S. healthcare system is in "complete chaos-disarray." Medical costs have increased significantly over the past 6 years with 70% increase for deductibles and 24% or more for health insurance premiums. All the while, workers earnings have either not increased or if they did, the pay raises were for less than the increase in the cost of medical care. The situation is unsustainable and the public wants the system fixed. This book offers ways of fixing the problems in healthcare. HEALTHCARE's OUT SICK - PREDICTING A CURE - Solutions that WORK !!!! first defines the "healthcare in crisis" problem. Through real patient experiences, the book describes the difficulties of getting through the maze of complexity among the plethora of "silo providers" which make up the industry. The heart of the book provides readers with a comprehensive solution that can work, a disruption that is necessary to provide Americans the medical care they need without the US public and healthcare providers and payors going into bankruptcy, insolvency or closure. This book delves into digitized medicine, payor and provider reimbursement models, and value-based healthcare delivery. It also includes a philosophy or mode of thinking and operation for the solutions that are needed for diagnosis-effective, cost-effective, and time-efficient healthcare delivery, of which digitized medicine, value-based care, and payor reimbursement modes are just some of the factors. The authors propose that the real solution involves having the patient at the center of the issues and changing from an archaic gold standard way of thinking to a "Predictive Analytic thinking" where one gets at the real truth by doing "real science" that in the end becomes effective not only for the population but for the individual person. This all leads to real person-centered and person-directed medicine and healthcare delivery.

Industry 4 0 Managing The Digital Transformation

Author : Alp Ustundag
ISBN : 9783319578705
Genre : Technology & Engineering
File Size : 25. 57 MB
Format : PDF
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This book provides a comprehensive guide to Industry 4.0 applications, not only introducing implementation aspects but also proposing a conceptual framework with respect to the design principles. In addition, it discusses the effects of Industry 4.0, which are reflected in new business models and workforce transformation. The book then examines the key technological advances that form the pillars of Industry 4.0 and explores their potential technical and economic benefits using examples of real-world applications. The changing dynamics of global production, such as more complex and automated processes, high-level competitiveness and emerging technologies, have paved the way for a new generation of goods, products and services. Moreover, manufacturers are increasingly realizing the value of the data that their processes and products generate. Such trends are transforming manufacturing industry to the next generation, namely Industry 4.0, which is based on the integration of information and communication technologies and industrial technology.The book provides a conceptual framework and roadmap for decision-makers for this transformation

Business Analytics Principles Concepts And Applications With Sas

Author : Marc J. Schniederjans
ISBN : 9780133989571
Genre : Computers
File Size : 75. 61 MB
Format : PDF
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Learn everything you need to know to start using business analytics and integrating it throughout your organization. Business Analytics Principles, Concepts, and Applications with SAS brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, this text demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. Business Analytics Principles, Concepts, and Applications with SAS will be a valuable resource for all beginning-to-intermediate level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.

Handbook Of Statistical Analysis And Data Mining Applications

Author : Robert Nisbet
ISBN : 0080912036
Genre : Mathematics
File Size : 39. 28 MB
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The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. Written "By Practitioners for Practitioners" Non-technical explanations build understanding without jargon and equations Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models Practical advice from successful real-world implementations Includes extensive case studies, examples, MS PowerPoint slides and datasets CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book

Practical Text Mining And Statistical Analysis For Non Structured Text Data Applications

Author : Gary Miner
ISBN : 9780123870117
Genre : Mathematics
File Size : 82. 38 MB
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Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. Winner of a 2012 PROSE Award in Computing and Information Sciences from the Association of American Publishers, this book presents a comprehensive how-to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities. The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. Extensive case studies, most in a tutorial format, allow the reader to 'click through' the example using a software program, thus learning to conduct text mining analyses in the most rapid manner of learning possible Numerous examples, tutorials, power points and datasets available via companion website on Elsevierdirect.com Glossary of text mining terms provided in the appendix

Sports Performance Measurement And Analytics

Author : Lorena Martin
ISBN : 013419330X
Genre : Business & Economics
File Size : 35. 13 MB
Format : PDF, ePub
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This is a thorough introduction to performance measurement and analytics for five major sports: football, soccer, baseball, basketball, and tennis. The only book of its kind, it provides a comprehensive overview of the most important concepts, rules, measurements, and statistics for each sport, while demonstrating real-world analytics applications for all of them. Author Lorena Martin is singularly well-qualified to write this guide. A lifelong athlete, she brings a combination of expertise in applied behavioral science, quantitative methodologies, and exercise physiology. Reflecting all this expertise, she discusses the rules of each game, shows how to think critically about athletic performance assessment, and helps you interpret statistical models in sports. You'll find practical, state-of-the-art guidance on predicting future outcomes, evaluating an athlete's market value, assessing draft picks, and much more. All example applications in Sports Performance Measurement and Analyticsbuild on open source programs, measurements, sports datasets, applied statistics, sports performance research, and predictive modeling work. Designed to meet the rapidly growing demand for sports data science in colleges and universities, this guide will appeal to everyone concerned with sports performance and analytics: students, teachers, sports analysts, physiologists, coaches, managers, general managers, and sophisticated fans.

Practical Data Science With R

Author : Nina Zumel
ISBN : 1617291560
Genre : Computers
File Size : 63. 62 MB
Format : PDF, Kindle
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Summary Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Business analysts and developers are increasingly collecting, curating, analyzing, and reporting on crucial business data. The R language and its associated tools provide a straightforward way to tackle day-to-day data science tasks without a lot of academic theory or advanced mathematics. Practical Data Science with R shows you how to apply the R programming language and useful statistical techniques to everyday business situations. Using examples from marketing, business intelligence, and decision support, it shows you how to design experiments (such as A/B tests), build predictive models, and present results to audiences of all levels. This book is accessible to readers without a background in data science. Some familiarity with basic statistics, R, or another scripting language is assumed. What's Inside Data science for the business professional Statistical analysis using the R language Project lifecycle, from planning to delivery Numerous instantly familiar use cases Keys to effective data presentations About the Authors Nina Zumel and John Mount are cofounders of a San Francisco-based data science consulting firm. Both hold PhDs from Carnegie Mellon and blog on statistics, probability, and computer science at win-vector.com. Table of Contents PART 1 INTRODUCTION TO DATA SCIENCE The data science process Loading data into R Exploring data Managing data PART 2 MODELING METHODS Choosing and evaluating models Memorization methods Linear and logistic regression Unsupervised methods Exploring advanced methods PART 3 DELIVERING RESULTS Documentation and deployment Producing effective presentations

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