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Sklearn Transformers & Estimators

Part I. Conceptual Foundations: The Scikit-learn Philosophy

• Chapter 1. Foundations of the Scikit-learn Design
• Chapter 2. Transformers: The Data Preprocessing Core
• Chapter 3. Estimators: The Predictive Interface

Part II. Workflow Composition and Automation

• Chapter 4. The Transformer Chain: Pipelines
• Chapter 5. The Column-wise View: ColumnTransformer

Part III. Model Optimization and Extension

• Chapter 6. Model Selection and Parameter Tuning
• Chapter 7. Advanced Transformer Mechanics
• Chapter 8. Feature Engineering and Data Flow in Practice

Part IV. Mastery and Deployment

• Chapter 9. Internals and Meta-Estimators
• Chapter 10. Debugging, Visualization, and Interpretation
• Chapter 11. Beyond the Basics
• Chapter 12. Case Studies