Data Mining for the Masses

Business analytics

ISBN:

978-1-959142-65-2

Data Mining for the Masses

Matt North, EdD

This resource introduces students to data mining using the CRISP-DM methodology. It is intended for students and business professionals who are interested in using information systems and technologies to solve organizational problems by mining data, but who may not have a background in computer science. Students will learn the concepts and techniques required to successfully mine data in AI Studio, R, and Python.

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About the Author Chapter 1: Introduction to Data Mining and CRISP-DM Chapter 2: Organizational Understanding and Data Understanding Chapter 3: Data Preparation Chapter 4: Correlational Methods Chapter 5: Association Rules Chapter 6: k-Means Clustering Chapter 7: Predicting Categories Chapter 8: Linear Regression Chapter 9: Logistic Regression Chapter 10: Decision Trees Chapter 11: Neural Networks Chapter 12: Text Mining Chapter 13: Cross-Validation Chapter 14: Data Mining Ethics

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