Book 12 — MLOps & Production AI

Building and operating AI systems, not just training models.

Tooling

• Git/GitHub
• Linux
• Docker
• FastAPI & CI/CD
• Testing

Comprehensive Deep Dive:

• 📖 Production Tooling, Containerization & CI/CD Deep Dive

Serving & Pipelines

• Model serving & registry
• Experiment tracking (MLflow)
• Feature stores
• Data pipelines (Airflow)
• Kubernetes & cloud (AWS/Azure/GCP)

Comprehensive Deep Dive:

• 📖 Model Serving, Pipelines & Distributed Orchestration Deep Dive

Operations

• Monitoring, logging, observability
• Model & data drift
• Retraining
• A/B testing & canary deployments
• Cost & GPU infrastructure

Comprehensive Deep Dive:

• 📖 Model Monitoring, Observability & Automated Retraining Deep Dive

Mastery Roadmap

Each topic includes comprehensive mathematical formulations, architectural diagrams, runnable Python implementations from scratch, common debugging pitfalls, staff-level interview questions, and a 10-level mastery ladder.