Machine Learning Basics

Introduction to Machine Learning

• Welcome to Data Science

Asking Business Questions Machine Learning Can Answer

• Introduction to Asking Business Questions
• Example 1: Customer Lifetime Value (a Regression example)
• Example 2: Customer Retention (a Classification example)

Data Transformation Techniques

• Introduction to Data Transformation Techniques
• Variable Data Types in Machine Learning
• Encoding Categorical Variables in Math
• Feature Scaling
• Imputation
• Model Preprocessing

Correlation

• Considerations in Selecting Drivers: The Law of Parsimony & Data Leakage
• Correlation is not causation
• Correlation Matrix

Models & Scoring

• Model Types
• Regressions
• Ensembles
• Other Model Types
• Scoring Metrics
• Scoring Classification Models

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Model Explanation

• ROC Curve Explained
• An overview of Feature Importance
• Permutation Importance explained
• SHAP Importance explained
• Explore predictions with Scenarios

Glossary

• Accuracy
• Area Under Curve (AUC)
• Confusion Matrix
• Correlation
• Correlation Matrix
• F1 Score

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