• Title: Data Mining and Machine Learning: Fundamental Concepts and Algorithms
• Author(s) Mohammed J. Zaki, Wagner Meira, Jr.
• Publisher: Cambridge University Press; 2nd edition (March 12, 2020); eBook (Online Edition)
• Permission: For Personal Use Only
• Hardcover: 776 pages
• eBook: PDF Files
• Language: English
• ISBN-10: 1108473989
• ISBN-13: 978-1108473989
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Book Description

The fundamental algorithms in data mining and analysis form the basis for the emerging field of data science, which includes automated methods to analyze patterns and models for all kinds of data, with applications ranging from scientific discovery to business intelligence and analytics.

This textbook for senior undergraduate and graduate data mining courses provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification.

The book lays the basic foundations of these tasks, and also covers cutting-edge topics such as kernel methods, high-dimensional data analysis, and complex graphs and networks.

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• Amazon

• Data Analysis and Data Mining
• Machine Learning
• Statistics, Mathematical Statistics, and SAS Programming
• Probability, Stochastic Process, Queueing Theory, etc.

• Data Mining and Machine Learning: Fundamental Concepts and Algorithms (Mohammed J. Zaki, et al)
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