Predictive Analytics
Data Mining, Machine Learning and Data Science for Practitioners
By: Dursun Delen
About This Book
"Using predictive analytics techniques, decision-makers can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions. 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 both business professionals and students. 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"--
AI Overview
The book "Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners" by Dursun Delen is a comprehensive guide to predictive analytics, covering a wide range of topics from data mining to advanced machine learning techniques. Here is a detailed overview:
Key Themes
Data Mining and Machine Learning:
- The book provides a holistic approach to data mining processes and methods, including relevant data management techniques, tools, and metrics.
Advanced Techniques:
- It covers advanced text and web mining, big data integration, and various predictive algorithms drawn from traditional statistics and advanced machine learning.
Real-World Applications:
- The book includes real-world case studies and lessons from failed projects, providing practical insights into how predictive analytics can be applied in business settings.
Decision-Making:
- It emphasizes the use of predictive analytics to uncover hidden patterns and correlations in data, thereby improving decision-making processes.
Standardized Processes:
- The guide advocates for standardized processes and workflows to make more trustworthy predictions, which is crucial for business applications.
Predictive Tasks:
- It covers various predictive tasks such as classification, regression, and time-series forecasting, helping practitioners understand how to predict discrete outcomes, numeric values, and changes over time.
Cutting-Edge Techniques:
- The book explores advanced applications ranging from sentiment analysis to fraud detection, making it relevant for a broad range of industries.
Plot Summary
The book is structured to balance theory and practice. It begins with an introduction to the basics of predictive analytics and gradually moves on to more advanced topics. The author, Dursun Delen, uses intuitive conceptual illustrations, realistic example problems, and real-world case studies to help readers gain a practical understanding of the subject.
Critical Reception
While specific reviews are not provided in the search results, the book is widely recognized for its comprehensive coverage of predictive analytics. It is praised for its ability to bridge the gap between theoretical knowledge and practical application, making it a valuable resource for both business professionals and students.
Edition and Updates
The book is part of the Pearson Business Analytics Series and has been updated to reflect the latest advancements in the field. The second edition is available, which includes additional insights and case studies to keep the content current and relevant.
Availability
The book is available for purchase or rental from various online retailers, including RedShelf, Barnes & Noble, and Booktopia. It is also available for free shipping on non-marketplace orders and rental returns.