Getting started with MLflow for machine learning and AI development
Compute Ontario Colloquium
Note: all times are shown in the timezone in which each event occurs.
Date: 25 March 2026 @ 12:00 - 13:00
Timezone: Eastern Daylight Time
Duration: 1 hour
Reproducibility and experiment tracking are essential in machine learning workflows. MLflow is an open-source platform for experiment tracking and model management in machine learning and AI development. This webinar introduces MLflow with quickstart examples running on the clusters, focusing on a lightweight setup with local storage. The examples will be demonstrated in Jupyter notebooks and in batch jobs.
Keywords: Machine Learning, AI
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