Prescriptive Analytics
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Prescriptive Analytics
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Author : Dursun Delen
language : en
Publisher:
Release Date : 2019
Prescriptive Analytics written by Dursun Delen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Prescriptive Analytics
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Author : Dursun Delen
language : en
Publisher: FT Press
Release Date : 2019-10-21
Prescriptive Analytics written by Dursun Delen and has been published by FT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-21 with Business & Economics categories.
Make Better Decisions, Leverage New Opportunities, and Automate Decisioning at Scale Prescriptive analytics is more directly linked to successful decision-making than any other form of business analytics. It can help you systematically sort through your choices to optimize decisions, respond to new opportunities and risks with precision, and continually reflect new information into your decisioning process. In Prescriptive Analytics, analytics expert Dr. Dursun Delen illuminates the field’s state-of-the-art methods, offering holistic insight for both professionals and students. Delen’s end-to-end, all-inclusive approach covers optimization, simulation, multi-criteria decision-making methods, inference- and heuristic-based decisioning, and more. Balancing theory and practice, he presents intuitive conceptual illustrations, realistic example problems, and real-world case studies–all designed to deliver knowledge you can use. Discover where prescriptive analytics fits and how it improves decision-making Identify optimal solutions for achieving an objective within real-world constraints Analyze complex systems via Monte-Carlo, discrete, and continuous simulations Apply powerful multi-criteria decision-making and mature expert systems and case-based reasoning Preview emerging techniques based on deep learning and cognitive computing
Prescriptive Analytics
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Author : Jeffrey M. Keisler
language : en
Publisher: Springer Nature
Release Date : 2024-08-24
Prescriptive Analytics written by Jeffrey M. Keisler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-24 with Business & Economics categories.
This book combines the quantitative decision-informing techniques of management science and operations research with the data-centric techniques found throughout the world of analytics. The material uses only standard Excel spreadsheet features and functions for creating models. Using a step-by-step approach, readers learn a unified architecture for sensitivity, scenario, simulation, decision, and optimization analysis. Spreadsheets with numerous screenshots support visual, hands-on learning (and provide some surprising innovations). Special influence diagrams and non-intimidating but accurate terminology help explain the logic of the models and calculations. Well-structured chapters include guideposts, enrichment, and curated links to valuable external resources. Readers are encouraged to own their learning and think about future trajectories for themselves and the field. This book helps all readers quickly learn tools and concepts to use right away and to expand throughout a career. The book includes access to a companion website featuring workbooks and other valuable materials to support learning.
Hands On Prescriptive Analytics
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Author : Walter R. Paczkowski
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-10-17
Hands On Prescriptive Analytics written by Walter R. Paczkowski and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-17 with Business & Economics categories.
Business decisions in any context—operational, tactical, or strategic—can have considerable consequences. Whether the outcome is positive and rewarding or negative and damaging to the business, its employees, and stakeholders is unknown when action is approved. These decisions are usually made under the proverbial cloud of uncertainty. With this practical guide, data analysts, data scientists, and business analysts will learn why and how maximizing positive consequences and minimizing negative ones requires three forms of rich information: Descriptive analytics explores the results from an action—what has already happened. Predictive analytics focuses on what could happen. The third, prescriptive analytics, informs us what should happen in the future. While all three are important for decision-makers, the primary focus of this book is on the third: prescriptive analytics. Author Walter R. Paczkowski, Ph.D. shows you: The distinction among descriptive, predictive, and prescriptive analytics How predictive analytics produces a menu of action options How prescriptive analytics narrows the menu of action options The forms of prescriptive analytics: eight prescriptive methods Two broad classes of these methods: non-stochastic and stochastic How to develop prescriptive analyses for action recommendations Ways to use an appropriate tool-set in Python
Applied Predictive Analytics
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Author : Dean Abbott
language : en
Publisher: John Wiley & Sons
Release Date : 2014-03-31
Applied Predictive Analytics written by Dean Abbott and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-31 with Computers categories.
Learn the art and science of predictive analytics — techniques that get results Predictive analytics is what translates big data into meaningful, usable business information. Written by a leading expert in the field, this guide examines the science of the underlying algorithms as well as the principles and best practices that govern the art of predictive analytics. It clearly explains the theory behind predictive analytics, teaches the methods, principles, and techniques for conducting predictive analytics projects, and offers tips and tricks that are essential for successful predictive modeling. Hands-on examples and case studies are included. 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 achieve real, pragmatic solutions Explains methods, principles, and techniques for conducting predictive analytics projects from start to finish Illustrates each technique with hands-on examples and includes as series of in-depth case studies that apply predictive analytics to common business scenarios A companion website provides all the data sets used to generate the examples as well as a free trial version of software Applied Predictive Analytics arms data and business analysts and business managers with the tools they need to interpret and capitalize on big data.
Predictive Analytics For Human Resources
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Author : Jac Fitz-enz
language : en
Publisher: John Wiley & Sons
Release Date : 2014-07-28
Predictive Analytics For Human Resources written by Jac Fitz-enz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-28 with Business & Economics categories.
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. The book explains the basics of every business—the vision, the brand, and the culture, and shows how predictive analytics supports them. The authors put the focus on the fundamentals of predictability and include a framework of logical questions to help set up an analytic program or project, then follow up by offering a clear explanation of statistical applications. Predictive Analytics for Human Resources is a how-to guide filled with practical and targeted advice. The book starts with the basic idea of engaging in predictive analytics and walks through case simulations showing statistical examples. In addition, this important resource addresses the topics of internal coaching, mentoring, and sponsoring and includes information on how to recruit a sponsor. In the book, you'll find: A comprehensive guide to developing and implementing a human resource analytics project Illustrative examples that show how to go to market, develop a leadership model, and link it to financial targets through causal modeling Explanations of the ten steps required in building an analytics function How to add value through analysis of systems such as staffing, training, and retention For anyone who wants to launch an analytics project or program for HR, this complete guide provides the information and instruction to get started the right way.
Predictive Analytics For Toxicology
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Author : Luis G. Valerio, Jr.
language : en
Publisher: CRC Press
Release Date : 2024-08-13
Predictive Analytics For Toxicology written by Luis G. Valerio, Jr. and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-13 with Science categories.
Predictive data science is already in use in many fields, but its application in toxicology is new and sought after by non-animal alternative testing initiatives. Predictive Analytics for Toxicology: Applications in Discovery Science provides a comprehensive overview of the application of predictive analytics in the field of toxicology, highlighting its role and applications in discovery science. This book addresses the challenges of accurately predicting high-level endpoints of toxicity and explores the use of computational and artificial intelligence research to automate predictive toxicology. It underscores the importance of predictive toxicology in proposing and explaining adverse outcomes resulting from human exposures to specific toxicants, especially when experimental and observational data on the toxicant are incomplete or unavailable. Key features: Includes a plain language description of predictive analytics in toxicology adding an overview of the wide range of applications Examines the science of prediction, computational models as an automated science and comprehensive discussions on concepts of machine learning Opens the hood on AI and its applications in toxicology Features coverage on how in silico toxicity predictions are translational science tools The book integrates strategies and practices of predictive toxicology and offers practical information that students and professionals of the toxicology, chemical, and pharmaceutical industries will find essential. It fulfills the expectations of student researchers seeking to learn predictive analytics in toxicology. This book will energize scientists to conduct predictive toxicology modeling using artificial intelligence and machine learning, and inspire students and seasoned scientists interested in automated science to pick up new research using predictive in silico models to evaluate chemical-induced toxicity. With its focus on practical applications and real-world examples, this book serves as a guide for navigating the complex issues and practices of discovery toxicology. It is an essential resource for those interested in computer-based methods in toxicology, providing valuable insights into the use of predictive analytics.
Decision Intelligence Analytics And The Implementation Of Strategic Business Management
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Author : P. Mary Jeyanthi
language : en
Publisher: Springer Nature
Release Date : 2022-01-01
Decision Intelligence Analytics And The Implementation Of Strategic Business Management written by P. Mary Jeyanthi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Technology & Engineering categories.
This book presents a framework for developing an analytics strategy that includes a range of activities, from problem definition and data collection to data warehousing, analysis, and decision making. The authors examine best practices in team analytics strategies such as player evaluation, game strategy, and training and performance. They also explore the way in which organizations can use analytics to drive additional revenue and operate more efficiently. The authors provide keys to building and organizing a decision intelligence analytics that delivers insights into all parts of an organization. The book examines the criteria and tools for evaluating and selecting decision intelligence analytics technologies and the applicability of strategies for fostering a culture that prioritizes data-driven decision making. Each chapter is carefully segmented to enable the reader to gain knowledge in business intelligence, decision making and artificial intelligence in a strategic management context.
Practical Predictive Analytics And Decisioning Systems For Medicine
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Author : Gary D. Miner
language : en
Publisher: Academic Press
Release Date : 2014-09-27
Practical Predictive Analytics And Decisioning Systems For Medicine written by Gary D. Miner and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-27 with Computers categories.
With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. 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.Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions. - Includes models and applications of predictive analytics why they are important and how they can be used in healthcare and medical research - Provides real world step-by-step tutorials to help beginners understand how the predictive analytic processes works and to successfully do the computations - Demonstrates methods to help sort through data to make better observations and allow you to make better predictions
Predictive Analytics For Mechanical Engineering A Beginners Guide
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Author : Parikshit N. Mahalle
language : en
Publisher: Springer Nature
Release Date : 2023-08-16
Predictive Analytics For Mechanical Engineering A Beginners Guide written by Parikshit N. Mahalle and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-16 with Technology & Engineering categories.
This book focus on key component required for building predictive maintenance model. The current trend of Maintenance 4.0 leans towards the preventive mechanism enabled by predictive approach and condition-based smart maintenance. The intelligent decision support, earlier detection of spare part failure, fatigue detection is the main slices of intelligent and predictive maintenance system (PMS) leading towards Maintenance 4.0 This book presents prominent use cases of mechanical engineering using PMS along with the benefits. Basic understanding of data preparation is required for development of any AI application; in view of this, the types of the data and data preparation processes, and tools are also presented in this book.