Experimentation
Lifecycle stages:
The experimentation stage is where ideas are tested, models are prototyped, and configurations are explored. In Azure Machine Learning, this phase is designed to support rapid iteration while enabling you to track results for future reproducibility.
Documents available for this stage
📄️ Experiment Tracking
Using MLflow in Azure ML to track experiments.
📄️ Hyperparameter Tuning
Hyperparameter tuning using AzureML studio and Python SDK.