The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest. This book is about predictive analytics. Including comprehensive coverage of an array of predictive analytic tools and techniques, this book enables readers to harness patterns from past data, to make accurate and useful predictions that can be converted to business success. The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest. This uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. Found insideUnfortunately, both the analytics and AI communities have not done a great job in collaborating and communicating with each other to build the necessary synergies. This book bridges the gap between these two critical fields. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on prescriptive analytics. The book seeks to provide simple explanations and demonstration of some descriptive tools. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost–efficient manner. Found insideThis 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. Found insideThe purpose of this book is to provide a gentle and instructionally organized introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. Found insideThis book prepares your organization for these increas­ing demands by helping you do the following: Learn the ten defining strategies for a customer experience–focused company. The new edition of this textbook presents a practical, updated approach to predictive analytics for classroom learning. Found inside – Page iThis practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions. Found insideExploit the power of data in your business by building advanced predictive modeling applications with Python About This Book Master open source Python tools to build sophisticated predictive models Learn to identify the right machine ... This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning. There are three reasons for this shortfall. First, the volume of data is increasing much faster than the corresponding rise of our computational processing power (Kryder’s law > Moore’s law). With the help of this friendly guide, you'll discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data. Found insideThis book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or ... Throughout the book, Alberto Cordoba puts the spotlight on developing an understanding of business performance based on the extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based ... Found inside – Page viIt will then provide some practical examples of unsupervised learning. ... Lesson 4, Using Reinforcement Learning for Predictive Analytics, ... Found insideThe need for a systematic and methodological development of visual analytics was detected. This book aims at addressing this need. Found inside – Page i« Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of ... Found inside – Page iApplied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. In summary, this book includes: - An introduction to and some fundamentals for good analysis - A process outline to make analysis quick and effective - A description of some of the most used predictive models and methods, and how they ... The ability to successfully apply predictive analytics enables businesses to effectively interpret big data; essential for competition today This guide teaches not only the principles of predictive analytics, but also how to apply them to ... This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Make sense of your data and predict the unpredictable About This Book A unique book that centers around develop six key practical skills needed to develop and implement predictive analytics Apply the principles and techniques of predictive ... Found inside – Page iGoing beyond the theoretical foundation, this step-by-step book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis. -- " Predictive Analytics for Human Resources is designed to answer these and other vital questions. The book explains the basics of every business—the vision, the brand, and the culture, and shows how predictive analytics supports them. This textbook presents a practical approach to predictive analytics for classroom learning. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate ... Discover the breakthrough tool your company can use to make winning decisions This forward-thinking book addresses the emergence of predictive business analytics, how it can help redefine the way your organization operates, and many of the ... Found insideHow does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. While the text is biased against complex equations, a mathematical background is needed for advanced topics. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning. All the tools you need are available in Microsoft Excel 2016, and all the knowledge and skills are right here, in this book! This revised text highlights new and emerging technology, discusses the importance of analytic context for ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models ... Found inside – Page 3Examples of parametric models of supervised learning include multiple regression , logistic regression , discriminant analysis , generalized linear models ... This textbook presents a practical approach to predictive analytics for classroom learning. Found inside – Page 1This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and ... Data science is also the new look of marketing research. The best way to learn about marketing data science is to work through examples. This book provides a ready resource and reference guide for modeling techniques. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book will be beneficial to and can be read by any Data Science enthusiasts. Some familiarity with Python will be useful to get the most out of this book, but it is certainly not a prerequisite. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining. You’ll be able to: 1. With the help of this friendly guide, you'll discover the core of predictive analytics and get started putting it to use with readily available tools to collect and analyze data. This Revised Edition is updated with new sources throughout, and has been reorganized to be completely modular. Found insideMake 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 ... Found insideIt involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. The book begins with the statistical and linear algebra/matrix foundation of modeling methods, from distributions to cumulant and copula functions to Cornish–Fisher expansion and other useful but hard-to-find statistical techniques. 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