Author Description

Intro -- Copyright -- Table of Contents -- Preface -- Who Is This Book For? -- What's Not in the Book -- Code Samples -- Conventions Used in This Book -- O'Reilly Online Learning -- How to Contact Us -- Acknowledgments -- Chapter 1. The Need for Machine Learning Design Patterns -- What Are Design Patterns? -- How to Use This Book -- Machine Learning Terminology -- Models and Frameworks -- Data and Feature Engineering -- The Machine Learning Process -- Data and Model Tooling -- Roles -- Common Challenges in Machine Learning -- Data Quality -- Reproducibility -- Data Drift -- Scale -- Multiple Objectives -- Summary -- Chapter 2. Data Representation Design Patterns -- Simple Data Representations -- Numerical Inputs -- Categorical Inputs -- Design Pattern 1: Hashed Feature -- Problem -- Solution -- Why It Works -- Trade-Offs and Alternatives -- Design Pattern 2: Embeddings -- Problem -- Solution -- Why It Works -- Trade-Offs and Alternatives -- Design Pattern 3: Feature Cross -- Problem -- Solution -- Why It Works -- Trade-Offs and Alternatives -- Design Pattern 4: Multimodal Input -- Problem -- Solution -- Trade-Offs and Alternatives -- Summary -- Chapter 3. Problem Representation Design Patterns -- Design Pattern 5: Reframing -- Problem -- Solution -- Why It Works -- Trade-Offs and Alternatives -- Design Pattern 6: Multilabel -- Problem -- Solution -- Trade-Offs and Alternatives -- Design Pattern 7: Ensembles -- Problem -- Solution -- Why It Works -- Trade-Offs and Alternatives -- Design Pattern 8: Cascade -- Problem -- Solution -- Trade-Offs and Alternatives -- Design Pattern 9: Neutral Class -- Problem -- Solution -- Why It Works -- Trade-Offs and Alternatives -- Design Pattern 10: Rebalancing -- Problem -- Solution -- Trade-Offs and Alternatives -- Summary -- Chapter 4. Model Training Patterns -- Typical Training Loop.