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2️⃣ Model Monitoring and Data Drift with Production or Unlabeled Data

Once your model is in production, it is essential to monitor its health:
Production data monitoring with Galileo
Is there training<>production data drift? What unlabeled data should I select for my next training run? Is the model confidence dropping on an existing class in production? ...
To answer the above questions and more with Galileo, you will need:
  1. 1.
    Your unlabeled production data
  2. 2.
    Your model

⚡️Simply run an inference job on production data to view, inspect and select samples directly in the Galileo UI.

Here is what to expect:
• Get the list of drifted data samples out of the box
• Get the list of on the class boundary samples out of the box
• Quickly compare model confidence and class distributions between production and training runs
• Find similar samples to low confidence production data within less than a second
... and a lot more
How to run an inference job with Galileo? Start here