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DP-100 · Question #488

DP-100 Question #488: Real Exam Question with Answer & Explanation

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Train and deploy models

Question

You manage an Azure Machine Learning workspace. You build a custom model you must log with MLflow. The custom model includes the following: - The model is not natively supported by MLflow. - The model cannot be serialized in Pickle format. - The model source code is complex. - The Python library for the model must be packaged with the model. You need to create a custom model flavor to enable logging with MLflow. What should you use?

Options

  • Amodel loader
  • Bartifacts
  • Cmodel wrapper
  • Dcustom signatures

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Topics

#MLflow#Custom Models#Model Logging#Model Flavors
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