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What is the purpose of A/B testing in MLOps?

Practice Questions

Q1
What is the purpose of A/B testing in MLOps?
  1. To compare two versions of a model
  2. To train models faster
  3. To clean data
  4. To visualize model performance

Questions & Step-by-Step Solutions

What is the purpose of A/B testing in MLOps?
  • Step 1: Understand that A/B testing is a method used to compare two different versions of something.
  • Step 2: In MLOps, this 'something' refers to two versions of a machine learning model.
  • Step 3: Create two versions of the model: Version A and Version B.
  • Step 4: Deploy both versions in a real-world environment where they can be tested.
  • Step 5: Split the audience or data so that half of the users see Version A and the other half see Version B.
  • Step 6: Collect data on how each version performs based on specific metrics (like accuracy, user engagement, etc.).
  • Step 7: Analyze the results to see which version performed better.
  • Step 8: Use the findings to decide which model to keep or improve.
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