Exam DP-100 topic 3 question 100 discussion

Experiment and Run classes serve different purposes: Experiment: An Experiment in Azure Machine Learning is a container for a series of trials, or Runs. It’s a way to organize and group your machine learning work. You can have multiple runs under an experiment, each representing a different trial in your machine learning workflow. For example, you might create an experiment to test different algorithms on a dataset, with each run representing a trial with a specific algorithm. Run: A Run in Azure Machine Learning represents a single trial in an experiment. It’s an individual execution of a script or pipeline, and it can be used to monitor the progress of an experiment run, log metrics, store output files, and more. Each run has a unique identifier within its parent experiment. Experiment as a project or folder that contains related runs, and a Run as an individual trial or task within that project.