Patel nitin r (33 Ergebnisse)

Hardcover. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Zustand: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Hardcover. Zustand: Fair. 1. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

Zustand: Good. 1 Edition. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: Very Good. 1 Edition. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: New.

Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.…

Hardcover. Zustand: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Hardcover. Zustand: Brand New. 2nd edition. 672 pages. 10.28x7.20x1.18 inches. In Stock.

Hardcover. Zustand: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Softcover. Zustand: gut. 2008. Data Mining for Business IntelligenceConcepts, Techniques, and Applications in Microsoft Office Excel with XLMiner von Nitin R. Patel and Peter C. Bruce Galit Shmueli (Autor) In englischer Sprache. pages.

Hardcover. Zustand: Brand New. 2nd edition. 384 pages. 10.00x7.00x1.00 inches. In Stock.

Zustand: NEW.

Zustand: NEW.

Zustand: New. In English.

Zustand: New.

Zustand: New. In English.

Zustand: New.

Zustand: New. In English.

Hardcover. Zustand: Brand New. 2nd edition. 624 pages. 10.24x7.32x1.18 inches. In Stock.

Zustand: New. In English.

Zustand: Very Good.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 560 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Buch. Zustand: Neu. Neuware - Machine Learning for Business AnalyticsMachine 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 RapidMiner 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 seventh edition of Machine Learning for Business Analytics, and the first using RapidMiner software. This edition also includes:\* A new co-author, Amit Deokar, who brings experience teaching business analytics courses using RapidMiner\* Integrated use of RapidMiner, an open-source machine learning platform that has become commercially popular in recent years\* 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 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 - 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.…