{"title":"Galit Shmueli","description":"\u003cp\u003eDelve into the world of statistical modelling and data mining with Galit Shmueli's insightful books. Perfect for students and professionals, explore practical approaches to data analysis and forecasting.\u003c\/p\u003e","products":[{"product_id":"data-mining-for-business-analytics-book-galit-shmueli-9781119549840","title":"Data Mining for Business Analytics","description":"Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration   Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities.   This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes:     A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions   Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.   “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.”   —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":49733339971857,"sku":"NGR9781119549840","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":51694907195665,"sku":"CIN1119549841VG","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ GOOD \/ SBYB","offer_id":51829826879761,"sku":"CIN1119549841G","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ NEW \/ INGRAM","offer_id":51915278844177,"sku":"NIN9781119549840","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":52082413142289,"sku":"GOR014480195","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52475943813393,"sku":"NLS9781119549840","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1119549841.jpg?v=1766656651"},{"product_id":"machine-learning-for-business-analytics-book-galit-shmueli-9781119829836","title":"Machine Learning for Business Analytics","description":"MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning—also known as data mining or predictive 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 with Analytic Solver® Data Mining provides a comprehensive introduction and an overview of this methodology. The fourth edition of this best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, time series forecasting and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques.   This fourth edition of Machine Learning for Business Analytics also includes:     An expanded chapter on deep learning A new chapter on experimental feedback techniques, including A\/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions   This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":49741015712017,"sku":"NGR9781119829836","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ GOOD \/ SBYB","offer_id":52947063865617,"sku":"CIN1119829836G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ WELL_READ \/ SBYB","offer_id":53270592192785,"sku":"CIN1119829836A","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1119829836.jpg?v=1751366774"},{"product_id":"machine-learning-for-business-analytics-book-galit-shmueli-9781119903833","title":"Machine Learning for Business Analytics","description":"MACHINE LEARNING FOR BUSINESS ANALYTICS An up-to-date introduction to a market-leading platform for data analysis and machine learning   Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. offers an accessible and engaging introduction to machine learning. It provides concrete examples and case studies to educate new users and deepen existing users’ understanding of their data and their business. Fully updated to incorporate new topics and instructional material, this remains the only comprehensive introduction to this crucial set of analytical tools specifically tailored to the needs of businesses.   Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. readers will also find:     Updated material which improves the book’s usefulness as a reference for professionals beyond the classroom Four new chapters, covering topics including Text Mining and Responsible Data Science An updated companion website with data sets and other instructor resources: www.jmp.com\/dataminingbook A guide to JMP Pro's new features and enhanced functionality   Machine Learning for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, 2nd ed. is ideal for students and instructors of business analytics and data mining classes, as well as data science practitioners and professionals in data-driven industries.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":49745613324561,"sku":"NGR9781119903833","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ GOOD \/ SBYB","offer_id":52327829766417,"sku":"CIN1119903831G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":52889778979089,"sku":"CIN1119903831VG","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1119903831.jpg?v=1751016142"},{"product_id":"machine-learning-for-business-analytics-book-galit-shmueli-9781119835172","title":"Machine Learning for Business Analytics","description":"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 case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques.   This is the second R edition of Machine Learning for Business Analytics. This edition also includes:     A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using R An expanded chapter focused on discussion of deep learning techniques A new chapter on experimental feedback techniques including A\/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions   This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":49748163100945,"sku":"NGR9781119835172","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ GOOD \/ SBYB","offer_id":50982272565521,"sku":"CIN1119835178G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":51883959320849,"sku":"CIN1119835178VG","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ WELL_READ \/ SBYB","offer_id":53439180275985,"sku":"CIN1119835178A","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1119835178.jpg?v=1750709921"},{"product_id":"practical-time-series-forecasting-book-galit-shmueli-9780991576654","title":"Practical Time Series Forecasting","description":"\u003cp\u003e\u003cem\u003ePractical Time Series Forecasting: A Hands-On Guide, Third Edition\u003c\/em\u003e provides an applied approach to time-series forecasting. Forecasting is an essential component of predictive analytics. The book introduces popular forecasting methods and approaches used in a variety of business applications.\u003c\/p\u003e \u003cp\u003eThe book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods to develop effective forecasting solutions that extract business value from time-series data.\u003c\/p\u003e \u003cp\u003eFeaturing improved organization and new material, the \u003cem\u003eSecond Edition\u003c\/em\u003e also includes: \u003c\/p\u003e \u003cul\u003e \u003cli\u003ePopular forecasting methods including smoothing algorithms, regression models, and neural networks\u003c\/li\u003e \u003cli\u003eA practical approach to evaluating the performance of forecasting solutions\u003c\/li\u003e \u003cli\u003eA business-analytics exposition focused on linking time-series forecasting to business goals\u003c\/li\u003e \u003cli\u003eGuided cases for integrating the acquired knowledge using real data\u003c\/li\u003e \u003cli\u003eEnd-of-chapter problems to facilitate active learning\u003c\/li\u003e \u003cli\u003eA companion site with data sets, learning resources, and instructor materials (solutions to exercises, case studies)\u003c\/li\u003e \u003cli\u003eGlobally-available textbook, available in both softcover and Kindle formats\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cem\u003ePractical Time Series Forecasting: A Hands-On Guide, Third Edition\u003c\/em\u003e is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, finance and management.\u003c\/p\u003e \u003cp\u003eFor more information, visit forecastingbook.com\u003c\/p\u003e","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":49758054285585,"sku":"CIN0991576659G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ NEW \/ INGRAM","offer_id":51011188326673,"sku":"NIN9780991576654","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0991576659.jpg?v=1750948886"},{"product_id":"data-mining-for-business-analytics-book-galit-shmueli-9781118729274","title":"Data Mining for Business Analytics","description":"An applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.   Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data.   Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes:     Real-world examples to build a theoretical and practical understanding of key data mining methods  End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https:\/\/www.dataminingbook.com Free 140-day license to use XLMiner for Education software   Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology.     Praise for the Second Edition   \"…full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing.\"– Research Magazine   \"Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature.\" – ComputingReviews.com  \"Excellent choice for business analysts...The book is a perfect fit for its intended audience.\"  – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization   Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare.  She has authored over 70 journal articles, books, textbooks and book chapters.   Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley.   Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.","brand":"WoB","offers":[{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":49972270137617,"sku":"CIN1118729277VG","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ GOOD \/ SBYB","offer_id":50157789937937,"sku":"CIN1118729277G","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1118729277.jpg?v=1751301706"},{"product_id":"data-mining-for-business-intelligence-book-galit-shmueli-9780470526828","title":"Data Mining for Business Intelligence","description":"Praise for the First Edition \" full of vivid and thought-provoking anecdotes needs to be read by anyone with a serious interest in research and marketing.\" Research magazine \"Shmueli et al. have done a wonderful job in presenting the field of data mining a welcome addition to the literature.\" computingreviews.com Incorporating a new focus on data visualization and time series forecasting, Data Mining for Business Intelligence, Second Edition continues to supply insightful, detailed guidance on fundamental data mining techniques. This new edition guides readers through the use of the Microsoft Office Excel add-in XLMiner for developing predictive models and techniques for describing and finding patterns in data. From clustering customers into market segments and finding the characteristics of frequent flyers to learning what items are purchased with other items, the authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods, including classification, prediction, and affinity analysis as well as data reduction, exploration, and visualization. The Second Edition now features: * Three new chapters on time series forecasting, introducing popular business forecasting methods including moving average, exponential smoothing methods; regression-based models; and topics such as explanatory vs. predictive modeling, two-level models, and ensembles * A revised chapter on data visualization that now features interactive visualization principles and added assignments that demonstrate interactive visualization in practice * Separate chapters that each treat k-nearest neighbors and Naive Bayes methods * Summaries at the start of each chapter that supply an outline of key topics The book includes access to XLMiner, allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Each chapter concludes with exercises that allow readers to assess their comprehension of the presented material. The final chapter includes a set of cases that require use of the different data mining techniques, and a related Web site features data sets, exercise solutions, PowerPoint slides, and case solutions. Data Mining for Business Intelligence, Second Edition is an excellent book for courses on data mining, forecasting, and decision support systems at the upper-undergraduate and graduate levels. It is also a one-of-a-kind resource for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.","brand":"WoB","offers":[{"title":"US \/ WELL_READ \/ SBYB","offer_id":50262491136273,"sku":"CIN0470526823A","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":50834488197393,"sku":"CIN0470526823VG","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ VERY_GOOD \/ INTERNAL","offer_id":51395626696977,"sku":"GOR010264236","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ GOOD \/ SBYB","offer_id":52104212414737,"sku":"CIN0470526823G","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0470526823.jpg?v=1750942636"},{"product_id":"data-mining-for-business-intelligence-book-galit-shmueli-9780470084854","title":"Data Mining for Business Intelligence","description":"Learn how to develop models for classification, prediction, and customer segmentation with the help of \"Data Mining for Business Intelligence\". In today's world, businesses are becoming more capable of accessing their ideal consumers, and an understanding of data mining contributes to this success. \"Data Mining for Business Intelligence\", which was developed from a course taught at the Massachusetts Institute of Technology's Sloan School of Management, and the University of Maryland's Smith School of Business, uses real data and actual cases to illustrate the applicability of data mining intelligence to the development of successful business models. Featuring XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of data mining techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples are provided to motivate learning and understanding. \"Data Mining for Business Intelligence\" provides both a theoretical and practical understanding of the key methods of classification, prediction, reduction, exploration, and affinity analysis. It features a business decision-making context for these key methods. It illustrates the application and interpretation of these methods using real business cases and data. This book helps readers understand the beneficial relationship that can be established between data mining and smart business practices, and is an excellent learning tool for creating valuable strategies and making wiser business decisions.","brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50285450854673,"sku":"CIN0470084855G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ WELL_READ \/ SBYB","offer_id":53439439700241,"sku":"CIN0470084855A","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/0470084855.jpg?v=1750782649"},{"product_id":"practical-time-series-forecasting-book-galit-shmueli-9781468053456","title":"Practical Time Series Forecasting","description":null,"brand":"WoB","offers":[{"title":"US \/ GOOD \/ SBYB","offer_id":50385351803153,"sku":"CIN1468053450G","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":51744466239761,"sku":"CIN1468053450VG","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1468053450.jpg?v=1750923765"},{"product_id":"practical-risk-analysis-for-project-planning-book-galit-shmueli-9780991576685","title":"Practical Risk Analysis for Project Planning","description":"\u003cp\u003eProjects are investments of resources for achieving a particular objective or set of objectives. Resources include time, money, manpower, and sometimes lives. Objectives include financial gain, social and health benefits, national goals, educational and scientific achievements, and reduction of suffering, among many others. Projects are undertaken by large and small organizations, by governments, non-profit organizations, private businesses, and by individuals. Determining whether to execute a project, or which project to execute among a set of possibilities is often a challenge with high stakes. Assessing the potential outcomes of a project can therefore be detrimental, leading to the importance of making informative decisions.\u003c\/p\u003e\u003cp\u003e\u003cb\u003ePractical Risk Analysis for Project Planning\u003c\/b\u003e is a hands-on introduction to integrating numerical data and domain knowledge into popular spreadsheet software such as Microsoft Excel or Google Spreadsheets, to arrive at informed project-planning decisions. 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Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time-series data.\u003c\/p\u003e \u003cp\u003eFeaturing improved organization and new material, the \u003cem\u003eSecond Edition\u003c\/em\u003e also includes: \u003c\/p\u003e \u003cul\u003e \u003cli\u003ePopular forecasting methods including smoothing algorithms, regression models, and neural networks\u003c\/li\u003e \u003cli\u003eA practical approach to evaluating the performance of forecasting solutions\u003c\/li\u003e \u003cli\u003eA business-analytics exposition focused on linking time-series forecasting to business goals\u003c\/li\u003e \u003cli\u003eGuided cases for integrating the acquired knowledge using real data\u003c\/li\u003e \u003cli\u003eEnd-of-chapter problems to facilitate active learning\u003c\/li\u003e \u003cli\u003eA companion site with data sets, R code, learning resources, and instructor materials (solutions to exercises, case studies)\u003c\/li\u003e \u003cli\u003eGlobally-available textbook, available in both softcover and Kindle formats\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cem\u003ePractical Time Series Forecasting with R: A Hands-On Guide, Second Edition\u003c\/em\u003e is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. 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The book introduces popular forecasting methods and approaches used in a variety of business applications.\u003c\/p\u003e \u003cp\u003eThe book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods to develop effective forecasting solutions that extract business value from time-series data.\u003c\/p\u003e \u003cp\u003eFeaturing improved organization and new material, the \u003cem\u003eSecond Edition\u003c\/em\u003e also includes: \u003c\/p\u003e \u003cul\u003e \u003cli\u003ePopular forecasting methods including smoothing algorithms, regression models, and neural networks\u003c\/li\u003e \u003cli\u003eA practical approach to evaluating the performance of forecasting solutions\u003c\/li\u003e \u003cli\u003eA business-analytics exposition focused on linking time-series forecasting to business goals\u003c\/li\u003e \u003cli\u003eGuided cases for integrating the acquired knowledge using real data\u003c\/li\u003e \u003cli\u003eEnd-of-chapter problems to facilitate active learning\u003c\/li\u003e \u003cli\u003eA companion site with data sets, learning resources, and instructor materials (solutions to exercises, case studies)\u003c\/li\u003e \u003cli\u003eGlobally-available textbook, available in both softcover and Kindle formats\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cem\u003ePractical Time Series Forecasting: A Hands-On Guide, Third Edition\u003c\/em\u003e is the perfect textbook for upper-undergraduate, graduate and MBA-level courses as well as professional programs in data science and business analytics. The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, finance and management.\u003c\/p\u003e \u003cp\u003eFor more information, visit forecastingbook.com\u003c\/p\u003e","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51089028350225,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ GARDNERS","offer_id":51089028940049,"sku":"NGR9780997847932","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/099784793X.jpg?v=1751046562"},{"product_id":"machine-learning-for-business-analytics-book-galit-shmueli-9781394286799","title":"Machine Learning for Business Analytics","description":"Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python is a comprehensive introduction to and an overview of the methods that underlie modern AI. This best-selling textbook covers both statistical and machine learning (AI) algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, network analytics and generative AI. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques.   This is the second Python edition of Machine Learning for Business Analytics. This edition also includes:     A new chapter on generative AI (large language models or LLMs, and image generation) An expanded chapter on deep learning A new chapter on experimental feedback techniques including A\/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter of cases demonstrating applications for the machine learning techniques End-of-chapter exercises with data A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions   This textbook is an ideal resource for upper-level undergraduate and graduate level courses in AI, data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":51604410401041,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ GARDNERS","offer_id":51604410597649,"sku":"NGR9781394286799","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1394286791.jpg?v=1767354385"},{"product_id":"practical-acceptance-sampling-book-galit-shmueli-9780991576678","title":"Practical Acceptance Sampling","description":"\u003cb\u003eNew to the second edition: \u003c\/b\u003e A section on Acceptance-on-Zero plans, additional screenshots from the newly-designed SQCOnline.com with several new calculators, and improved book design for enhanced readability.\u003cp\u003e\u003cb\u003ePractical Acceptance Sampling\u003c\/b\u003e is a hands-on introduction to the inspection of products and services for quality assurance using statistically-based sampling plans.\u003c\/p\u003e\u003cp\u003eIn today's era of global supply chains, the path from raw materials to final product often takes place over multiple companies and across multiple continents. Acceptance sampling is key in the 21st century environment.\u003c\/p\u003e\u003cp\u003eAcceptance sampling plans provide criteria and decision rules for determining whether to accept or reject a batch based on a sample. They are therefore widely used by manufacturers, suppliers, contractors and subcontractors, and service providers in a wide range of industries.\u003c\/p\u003e\u003cp\u003eThe book introduces readers to the most popular sampling plans, including Military Standards and civilian ISO and ANSI\/ASQC\/BS standards. It covers the design, choice and performance evaluation of different types of plans, including single- and double-stage plans, rectifying and non-rectifying plans, plans for pass\/fail and continuous measurements, continuous sampling plans, and more.\u003c\/p\u003e\u003cp\u003e\u003cb\u003ePractical Acceptance Sampling\u003c\/b\u003e is suitable for courses on quality control and for quality practitioners with basic knowledge of statistics. 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