MLOps¶ ¶ ¶ ¶ Chapter 1: ML Problem Framing¶ Chapter 2: The MLOps Blueprint & Operational Strategy¶ Chapter 2a: ML Platforms¶ Chapter 3: Project Planning and Design¶ Chapter 4: Data Sourcing, Discovery, Platform¶ Chapter 5: Data Engineering and Pipelines¶ Chapter 6: Feature Engineering and Feature Stores¶ Chapter 7: Model Development & Iteration¶ Chapter 8: ML Training Pipelines¶ Chapter 9: ML Testing¶ Chapter 10: Model Deployment & Serving¶ Chapter 11: Monitoring, Observability, Drift, Interpretability¶ Chapter 12: Continual learning, Retraining, A/B Testing¶ Chapter 13: Governance, Ethics & The Human Element¶