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Show Notes
Data Mining for Business Analytics (Galit Shmueli)
- Amazon USA Store: https://www.amazon.com/dp/B01MYZU2PC?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Data-Mining-for-Business-Analytics-Galit-Shmueli.html
- Apple Books: https://books.apple.com/us/audiobook/data-mining-for-business-analytics-a-practical-no/id6813708120?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Data+Mining+for+Business+Analytics+Galit+Shmueli+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/B01MYZU2PC/
#JMPProanalytics #Classificationandregressiontrees #Upliftmodeling #Clusteranalysis #Timeseriesforecasting #DataMiningforBusinessAnalytics
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro is an applied textbook on predictive and descriptive analytics for business settings. Written by Galit Shmueli, Peter C. Bruce, Mia L. Stephens, and Nitin R. Patel, it uses JMP Pro software to connect statistical reasoning with hands-on analysis. The book is aimed primarily at advanced undergraduate and graduate students, while also serving analysts who need a structured introduction to common data mining workflows. Its scope extends from data visualization and dimension reduction to clustering, regression, classification, neural networks, ensemble methods, uplift modeling, and time series forecasting. Rather than treating algorithms as isolated technical objects, the text frames them as tools for questions such as predicting outcomes, assigning records to classes, segmenting populations, and identifying actionable patterns. Chapter summaries, exercises, case-based material, and companion datasets support active practice. The central purpose is to help readers select, build, assess, and communicate models in a business context, where predictive performance, interpretability, and decision consequences must be considered together.
- Amazon USA Store: https://www.amazon.com/dp/B01MYZU2PC?tag=9natree-20
- Amazon Worldwide Store: https://global.buys.trade/Data-Mining-for-Business-Analytics-Galit-Shmueli.html
- Apple Books: https://books.apple.com/us/audiobook/data-mining-for-business-analytics-a-practical-no/id6813708120?itsct=books_box_link&itscg=30200&ls=1&at=1001l3bAw&ct=9natree
- eBay: https://www.ebay.com/sch/i.html?_nkw=Data+Mining+for+Business+Analytics+Galit+Shmueli+&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339060787&customid=9natree&toolid=10001&mkevt=1
- Read more: https://english.9natree.com/read/B01MYZU2PC/
#JMPProanalytics #Classificationandregressiontrees #Upliftmodeling #Clusteranalysis #Timeseriesforecasting #DataMiningforBusinessAnalytics
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro is an applied textbook on predictive and descriptive analytics for business settings. Written by Galit Shmueli, Peter C. Bruce, Mia L. Stephens, and Nitin R. Patel, it uses JMP Pro software to connect statistical reasoning with hands-on analysis. The book is aimed primarily at advanced undergraduate and graduate students, while also serving analysts who need a structured introduction to common data mining workflows. Its scope extends from data visualization and dimension reduction to clustering, regression, classification, neural networks, ensemble methods, uplift modeling, and time series forecasting. Rather than treating algorithms as isolated technical objects, the text frames them as tools for questions such as predicting outcomes, assigning records to classes, segmenting populations, and identifying actionable patterns. Chapter summaries, exercises, case-based material, and companion datasets support active practice. The central purpose is to help readers select, build, assess, and communicate models in a business context, where predictive performance, interpretability, and decision consequences must be considered together.
