data mining business analytics von shmueli (16 Ergebnisse)

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Zustand: Very Good. Ships from the UK. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.

Hardcover. Zustand: Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.

Hardcover. Zustand: Very Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.

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Zustand: Sehr gut. Zustand: Sehr gut - Gepflegter, sauberer Zustand. 3. Auflage. | Seiten: 560 | Sprache: Englisch | Produktart: Bücher.

Hardcover. Zustand: Brand New. 574 pages. 10.00x7.00x1.00 inches. In Stock.

Hardcover. Zustand: Brand New. 4th edition. 589 pages. 10.00x7.00x1.25 inches. In Stock.

Buch. Zustand: Neu. Neuware - MACHINE LEARNING FOR BUSINESS ANALYTICSMachine 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(r) 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 solutionsThis 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.

Buch. Zustand: Neu. Neuware - 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 illustrationReaders 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 solutionsData 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.

Hardcover. Zustand: Brand New. har/psc edition. 544 pages. 11.00x8.00x1.25 inches. In Stock.

Hardcover. Zustand: Brand New. 3rd edition. 514 pages. 10.25x7.50x1.25 inches. In Stock.