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Chapter 1: Introduction to Machine Learning and R
Chapter 2: Data Preparation and Exploration
Chapter 3: Sampling and Resampling Techniques
Chapter 4: Visualization of Data
Chapter 5: Feature Engineering
Chapter 6: Machine Learning Models: Theory and Practice
Chapter 7: Machine Learning Model Evaluation.-Chapter 8: Model Performance Improvement
Chapter 9: Scalable Machine Learning and related technology.-

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