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Data Mining:: Practical Machine Learning Tools and Techniques (The Morgan Kaufmann Series in Data Management Systems)
Price: $43.44
(as of Dec 24,2024 12:28:25 UTC – Details)
ASIN : B004H1TB1W
Publisher : Morgan Kaufmann; 3rd edition (December 22, 2010)
Publication date : December 22, 2010
Language : English
File size : 9160 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 869 pages
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Customers find the book helpful for beginners and college students. They find the content useful and well-written. Readers appreciate the clear writing style and consider it a good value for money.
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Data Mining: Practical Machine Learning Tools and Techniques (The Morgan Kaufmann Series in Data Management Systems)
In today’s data-driven world, the ability to extract valuable insights from large datasets is more important than ever. Data mining, the process of uncovering patterns, trends, and correlations in data, is a powerful tool for businesses looking to make informed decisions and drive innovation.
One of the most comprehensive and widely-used resources for learning about data mining is the book “Data Mining: Practical Machine Learning Tools and Techniques” by Ian H. Witten, Eibe Frank, and Mark A. Hall. Part of The Morgan Kaufmann Series in Data Management Systems, this book provides a thorough introduction to the principles and techniques of data mining, with a focus on practical applications.
From basic concepts like data preprocessing and feature selection to advanced topics such as ensemble methods and deep learning, this book covers a wide range of machine learning techniques that can be applied to real-world problems. The authors provide clear explanations, practical examples, and hands-on exercises to help readers understand and apply these techniques in their own projects.
Whether you’re a data scientist, business analyst, or student looking to expand your knowledge of data mining, “Data Mining: Practical Machine Learning Tools and Techniques” is an invaluable resource. With its comprehensive coverage and practical approach, this book is sure to help you unlock the full potential of your data.
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