Designing Adaptable ML Systems#

[Video] - Introduction - Dec 13, 2022

[Video] - Adapting to data - Dec 13, 2022

[Video] - Changing distributions - Dec 13, 2022

[Video] - Lab: Adapting to data - Dec 13, 2022

[Video] - Right and wrong decisions - Dec 13, 2022

[Video] - System failure - Dec 13, 2022

[Video] - Concept drift - Dec 13, 2022

[Video] - Actions to mitigate concept drift - Dec 13, 2022

[Video] - TensorFlow data validation - Dec 13, 2022

[Video] - Components of TensorFlow data validation - Dec 13, 2022

[Video] - Lab Introduction: Introduction to TensorFlow Data Validation - Dec 13, 2022

[Lab] - Introduction to TensorFlow Data Validation

  • tfdv_basic_spending - lab, sol

[Video] - Lab Introduction: Advanced Visualizations with TensorFlow Data Validation - Dec 13, 2022

[Lab] - Advanced Visualizations with TensorFlow Data Validation

  • tfdv_advanced_taxi - lab, sol

[Video] - Mitigating training-serving skew through design - Dec 13, 2022

[Video] - Lab Introduction: Serving ML Predictions in Batch and Real Time - Dec 13, 2022

[Lab] - Serving ML Predictions in Batch and Real Time

  • serving_ml_prediction - lab, sol

[Video] - Lab Debrief: Serving ML Predictions in Batch and Real Time - Dec 13, 2022

[Video] - Diagnosing a production model - Dec 13, 2022