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Predictive Analytics and Data Mining: Concepts and Practice with Rapidminer Paperback – 10 December 2014

4.4 out of 5 stars 29 ratings
Edition: 1st

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Product description

Review

...an excellent introductory data science textbook to expose students to the essential concepts in predictive analytics. For the seasoned professional, it can serve as a handy reference book to choose the best predictive analytics tool for a given data set. --Computing Reviews

... ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining. --AnalyticBridge.com, 2015

If learning-by-doing is your mantra -- as well it should be for predictive analytics -- this book will jumpstart your practice. Covering a broad, foundational collection of techniques, authors Kotu and Deshpande deliver crystal-clear explanations of the analytical methods that empower organizations to learn from data. After each concept, screenshots make the 'how to' immediately concrete, revealing the steps needed to set things up and go; you're guided through real hands-on execution. --Eric Siegel, Ph.D., founder of Predictive Analytics World and author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die

The analytics that turns Big Data into actionable intelligence is no longer the exclusive realm of data scientists - it is impacting nearly every business function. Business intelligence is a significant competitive advantage, if applied properly. Gaining that advantage requires that business decision makers and data analyst have a good understanding of the available analytics tools and how to apply them. Predictive Analytics and Data Mining book provides an easy to understand framework of predictive analytics and data mining concepts. The framework is reinforced with examples and sample datasets that demonstrate how to apply the new tools to real-world problems. I highly recommend this book to anyone who wants a better understanding of how to make analytics a game changer for your organization--David Dowhan, President, TruSignal

Predictive analytics and insights has become the most critical skill-set in decision making and running the modern business. Predictive Analytics and Data Mining provides you the advanced concepts and practical implementation techniques to incorporate analytics in your business process. The two dozen data mining algorithms covered in this book forms the underpinnings of the field of business analytics that has transformed the way data is treated in business. So far, advanced analytics has been practiced only by select few. With your interest and this book, you can master it too. --Sy Fahimi, Operating Partner & Executive-in-Residence, Symphony Technology Group

There are two kinds of predictive analytics books. One kind gives a high level informal overview to those who just want to understand this field conceptually. Another kind gives a textbook technical introduction for the experts with extensive knowledge of statistics and computer science. Kotu and Deshpande's book is unusual because it strikes a nice balance. It can be understood by anyone who can understand basic computations of probability. The choice of RapidMiner is brilliant, since anyone who has used excel in the past can follow the hands-on examples, and learn to get more out of their data. The book does an excellent job of appealing to our intuitions about probabilities and then expanding on these intuitions to cover very advanced topics, such as decision trees and association rules. The material is accessible to anyone who took elementary statistics in college, even if college was many years ago. --Maria Stone, Vice President, Data and User Experience, Yahoo

About the Author

Vijay Kotu is Vice President of Analytics at ServiceNow. He leads the implementation of large-scale data platforms and services to support the company's enterprise business. He has led analytics organizations for over a decade with focus on data strategy, business intelligence, machine learning, experimentation, engineering, enterprise adoption, and building analytics talent. Prior to joining ServiceNow, he was Vice President of Analytics at Yahoo. He worked at Life Technologies and Adteractive where he led marketing analytics, created algorithms to optimize online purchasing behavior, and developed data platforms to manage marketing campaigns. He is a member of the Association of Computing Machinery and a member of the Advisory Board at RapidMiner.

Dr. Deshpande has extensive experience in working with companies ranging from startups to Fortune 5 in fields ranging from automotive, aerospace, retail, food, and manufacturing verticals delivering business analysis; designing and developing custom data products for implementing business intelligence, data science, and predictive analytics solutions. He was the Founder of SimaFore, a predictive analytics consulting company which was acquired by Soliton Inc., a provider of testing solutions for the semiconductor industry. He was also the Founding Co-chair of the annual Predictive Analytics World-Manufacturing conference. In his professional career he has worked with Ford Motor Company on their product development, with IBM at their IBM Watson Center of Competence, and with Domino's Pizza at their data science and artificial intelligence groups. He has a Ph.D. from Carnegie Mellon and an MBA from Ross School of Business, Michigan.

Product details

  • Publisher ‏ : ‎ Morgan Kaufmann Publishing; 1st edition (10 December 2014)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 448 pages
  • ISBN-10 ‏ : ‎ 0128014601
  • ISBN-13 ‏ : ‎ 978-0128014608
  • Dimensions ‏ : ‎ 19.05 x 2.57 x 23.5 cm
  • Customer Reviews:
    4.4 out of 5 stars 29 ratings

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Vijay Kotu is Senior Vice President of Analytics at ServiceNow. He leads the implementation of large-scale data platforms and services to support the company's enterprise business. He has led analytics organizations for over a decade with focus on data strategy, business intelligence, machine learning, experimentation, engineering, enterprise adoption, and building analytics talent. Prior to joining ServiceNow, he was Vice President of Analytics at Yahoo. He worked at Life Technologies and Adteractive where he led marketing analytics, created algorithms to optimize online purchasing behavior, and developed data platforms to manage marketing campaigns. He is a member of the Association of Computing Machinery and a member of the Advisory Board at RapidMiner.

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Mr. Brian D Meehan
5.0 out of 5 stars Superb easy to read book
Reviewed in the United Kingdom on 11 January 2018
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Roberto Breton Alberro
5.0 out of 5 stars Imprescindible
Reviewed in Spain on 19 June 2015
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Sandeep Raut
5.0 out of 5 stars Five Stars
Reviewed in India on 26 July 2015
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Amazon カスタマー
5.0 out of 5 stars Rapid tool guide for Machine Learning Practitioners: short key concepts and rich visual examples
Reviewed in Japan on 19 November 2017
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5.0 out of 5 stars Rapid tool guide for Machine Learning Practitioners: short key concepts and rich visual examples
Reviewed in Japan on 19 November 2017
This book is practical guide to realize data mining processes using rapid tool without programming, only click and drop. This includes a lot of figures and tables to help reader understand the algorithms and processors. On each chapter short column to introduce the key concept and typical algorithms using historical use cases for data miners and machine learning practitioners.
This book covers two dozens of typical algorithms, i.e. classification: Decision Tree, Naive Bayes, Artificial Neural Network, Support Vector Machine, regression: Linear & Logistic Regression, association analysis: Frequent Pattern Growth, clustering: k-means, Density Base Spatial Clustering Application with Noise(DBSCAN), Self-Organizing Map, anomaly detection: Distance & Density base, Local Outlier and feature selection: Principal Component Analysis(PCA), Forward selection, Backward Elimination and so forth.
This book shows how to implement these algorithms step by step among data mining process such as data handling, transforming, modeling and evaluation using powerful open source under ten thousands data examples: RapidMiner Studio Free version. It is possible to extend big data for millions of examples and multi-processors for rapid execution time to get the Middle and Large commercial version.
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William P Ross
4.0 out of 5 stars Well Designed Book On Data Mining and Predictions
Reviewed in the United States on 18 June 2016
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