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Top rated data mining books

Here are some top-rated data mining books, in no particular order, along with their average ratings and number of reviews on platforms like Amazon and Goodreads:

  1. "Data Mining: Practical Machine Learning Tools and Techniques" by Ian H. Witten and Eibe Frank (4.5/5, 200+ reviews) This book provides a comprehensive introduction to data mining, with a focus on practical techniques and tools.

  2. "Data Mining: Concepts and Techniques" by Jiawei Han, Micheline Kamber, and Jian Pei (4.5/5, 500+ reviews) This book covers the fundamental concepts of data mining, including data preprocessing, association rule mining, and clustering.

  3. "Pattern Recognition and Machine Learning" by Christopher M. Bishop (4.7/5, 200+ reviews) While not exclusively focused on data mining, this book provides a comprehensive introduction to machine learning and pattern recognition, which are essential components of data mining.

  4. "Data Mining for Business Intelligence" by Galit Shmueli, Nitin R. Patel, and Peter C. Bruce (4.3/5, 100+ reviews) This book focuses on applying data mining techniques to business problems, with case studies and examples from various industries.

  5. "Introduction to Data Mining" by Tan, Steinbach, and Kumar (4.2/5, 200+ reviews) This book provides a broad introduction to data mining, covering topics such as data preprocessing, clustering, and text mining.

  6. "Data Mining: A Tutorial-Based Approach" by Richard D. De Veaux, Paul F. Velleman, and David E. Bock (4.3/5, 50+ reviews) This book uses a tutorial-based approach to introduce data mining concepts, with a focus on practical applications and case studies.

  7. "Mining the Web: Discovering Knowledge from Hypertext Data" by Soumen Chakrabarti (4.4/5, 20+ reviews) This book focuses on web mining, covering topics such as web crawling, search engines, and web usage analysis.

  8. "Data Mining and Business Analytics with R" by Johannes Ledolter (4.4/5, 20+ reviews) This book provides an introduction to data mining and business analytics using the R programming language.

  9. "Data Mining: Multimedia, Soft Computing, and Bioinformatics" by Sushmita Mitra, Sankar K. Pal, and Pabitra Mitra (4.2/5, 20+ reviews) This book covers advanced data mining topics, including multimedia, soft computing, and bioinformatics.

  10. "Data Mining for Dummies" by Meta L. Brown (4.1/5, 50+ reviews) This book provides a beginner-friendly introduction to data mining, covering the basics of data mining and its applications.

Note: Ratings and review counts may vary depending on the platform and the time of checking.