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Data Mining: An Introduction
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Data Mining: An Introduction in Bloomington, MN
Current price: $70.00
Data Mining: An Introduction in Bloomington, MN
Current price: $70.00
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-The book covers a wide range of topics related to data mining, including deep learning, decision tree induction, association rule mining, analytical statistics techniques, clustering, and more.
-The book provides numerous case studies and examples that illustrate how data mining techniques can be applied in real-world settings, such as in banking, education, software engineering, and weather forecasting.
-The book emphasizes the importance of machine learning in data mining and provides a detailed discussion of various machine learning techniques, such as regression and classification.
-The book uses Python programming language and MapReduce algorithms to illustrate various data mining techniques, making it accessible to readers with programming experience.
-The book provides numerous case studies and examples that illustrate how data mining techniques can be applied in real-world settings, such as in banking, education, software engineering, and weather forecasting.
-The book emphasizes the importance of machine learning in data mining and provides a detailed discussion of various machine learning techniques, such as regression and classification.
-The book uses Python programming language and MapReduce algorithms to illustrate various data mining techniques, making it accessible to readers with programming experience.
-The book covers a wide range of topics related to data mining, including deep learning, decision tree induction, association rule mining, analytical statistics techniques, clustering, and more.
-The book provides numerous case studies and examples that illustrate how data mining techniques can be applied in real-world settings, such as in banking, education, software engineering, and weather forecasting.
-The book emphasizes the importance of machine learning in data mining and provides a detailed discussion of various machine learning techniques, such as regression and classification.
-The book uses Python programming language and MapReduce algorithms to illustrate various data mining techniques, making it accessible to readers with programming experience.
-The book provides numerous case studies and examples that illustrate how data mining techniques can be applied in real-world settings, such as in banking, education, software engineering, and weather forecasting.
-The book emphasizes the importance of machine learning in data mining and provides a detailed discussion of various machine learning techniques, such as regression and classification.
-The book uses Python programming language and MapReduce algorithms to illustrate various data mining techniques, making it accessible to readers with programming experience.
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