AIML Week: Modifying ML models when major events occur

Machine learning models are built and optimized based on a data set at a given point in time. If the underlying data behind the ML model changes quickly or dramatically, the model may have difficulty automatically adjusting and its accuracy could be impacted. This session provides best practices for monitoring, alerting, and retraining your ML models should a major event impact the data. We recommend this session to developers proficient in building, deploying, and monitoring machine learning models.