Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence

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Release : 2017-02-14
Genre : Computers
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Book Rating : 325/5 ( reviews)

Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence write by Trivedi, Shrawan Kumar. This book was released on 2017-02-14. Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence available in PDF, EPUB and Kindle. The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.

Advanced Data Mining Techniques

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Release : 2008-01-01
Genre : Business & Economics
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Book Rating : 17X/5 ( reviews)

Advanced Data Mining Techniques - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advanced Data Mining Techniques write by David L. Olson. This book was released on 2008-01-01. Advanced Data Mining Techniques available in PDF, EPUB and Kindle. This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.

Data Mining for Business Intelligence

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Release : 2006-12-11
Genre : Mathematics
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Book Rating : 855/5 ( reviews)

Data Mining for Business Intelligence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining for Business Intelligence write by Galit Shmueli. This book was released on 2006-12-11. Data Mining for Business Intelligence available in PDF, EPUB and Kindle. 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 Features a business decision-making context for these key methods 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.

Data Mining for Business Analytics

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Release : 2019-10-14
Genre : Mathematics
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Book Rating : 85X/5 ( reviews)

Data Mining for Business Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining for Business Analytics write by Galit Shmueli. This book was released on 2019-10-14. Data Mining for Business Analytics available in PDF, EPUB and Kindle. 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

Data Mining and Business Intelligence

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Release : 2001-01-01
Genre : Computers
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Book Rating : 037/5 ( reviews)

Data Mining and Business Intelligence - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining and Business Intelligence write by Stephan Kudyba. This book was released on 2001-01-01. Data Mining and Business Intelligence available in PDF, EPUB and Kindle. Annotation Provides an overview of data mining technology and how it is applied in a business environment. Material is not written in a technical style, but rather addresses the applied methodology behind implementing data mining techniques in the corporate environment. Explains how the technology evolved, overviews the methodologies that comprise the data mining spectrum, and looks at everyday business applications for data mining, in areas such as marketing and advertising promotions and pricing policies using econometric-based modeling, and using the Internet to help improve an organization's performance. Kudyba is an economic consultant. Hoptroff is an independent consultant with experience in data mining software. Annotation c. Book News, Inc., Portland, OR (booknews.com).