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Predictive Analytics
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Predictive Analytics : Data Mining, Machine Learning and Data Science for Practitioners

Book Details

Format Paperback / Softback
ISBN-10 0136738516
ISBN-13 9780136738510
Publisher Pearson Education (US)
Imprint Pearson FT Press
Country of Manufacture US
Country of Publication GB
Publication Date Jan 19th, 2021
Print length 448 Pages
Weight 690 grams
Dimensions 15.20 x 22.60 x 2.80 cms
Ksh 6,950.00
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In  Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for students. Using predictive analytics techniques, students can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions. Delen’s holistic approach covers all this, and more:
  • Data mining processes, methods, and techniques
  • The role and management of data
  • Predictive analytics tools and metrics
  • Techniques for text and web mining, and for sentiment analysis
  • Integration with cutting-edge Big Data approaches
Throughout, Delen promotes understanding by presenting numerous conceptual illustrations, motivational success stories, failed projects that teach important lessons, and simple, hands-on tutorials that set this guide apart from competitors.
Use Predictive Analytics to Uncover Hidden Patterns and Correlations and Improve Decision-Making


Using predictive analytics techniques, decision-makers can uncover hidden patterns and correlations in their data and leverage these insights to improve many key business decisions. In this thoroughly updated guide, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for both business professionals and students.


Delen provides a holistic approach covering key data mining processes and methods, relevant data management techniques, tools and metrics, advanced text and web mining, big data integration, and much more. Balancing theory and practice, Delen presents intuitive conceptual illustrations, realistic example problems, and real-world case studies—including lessons from failed projects. It is all designed to help you gain a practical understanding you can apply for profit.


* Leverage knowledge extracted via data mining to make smarter decisions
* Use standardized processes and workflows to make more trustworthy predictions
* Predict discrete outcomes (via classification), numeric values (via regression), and changes over time (via time-series forecasting)
* Understand predictive algorithms drawn from traditional statistics and advanced machine learning
* Discover cutting-edge techniques, and explore advanced applications ranging from sentiment analysis to fraud detection


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