1. Introducing the ML Workflow
  2. Hydrating the Data Lake
  3. Predicting the Future With Features
  4. Orchestrating the Data Continuum
  5. Casting a Deeper Net (Algorithms and Neural Networks)
  6. Iteration Makes Intelligence (Model Training and Tuning)
  7. Let George Take Over (AutoML in Action)
  8. Blue or Green (Model Deployment Strategies)
  9. Wisdom at Scale with Elastic Inference
  10. Adding Intelligence with Sensory Cognition
  11. AI for Industrial Automation
  12. Operationalized Model Assembly (MLOps and Best Practices)