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Exam Certified Machine Learning Professional All Questions

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Exam Certified Machine Learning Professional topic 1 question 12 discussion

Actual exam question from Databricks's Certified Machine Learning Professional
Question #: 12
Topic #: 1
[All Certified Machine Learning Professional Questions]

A data scientist has developed and logged a scikit-learn random forest model model, and then they ended their Spark session and terminated their cluster. After starting a new cluster, they want to review the feature_importances_ of the original model object.
Which of the following lines of code can be used to restore the model object so that feature_importances_ is available?

  • A. mlflow.load_model(model_uri)
  • B. client.list_artifacts(run_id)["feature-importances.csv"]
  • C. mlflow.sklearn.load_model(model_uri)
  • D. This can only be viewed in the MLflow Experiments UI
  • E. client.pyfunc.load_model(model_uri)
Show Suggested Answer Hide Answer
Suggested Answer: C 🗳️
by BokNinja at Dec. 19, 2023, 5:30 a.m.

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Alishahab70
9 months, 3 weeks ago
Selected Answer: C
C is correct
upvoted 1 times
...
hugodscarvalho
10 months ago
Selected Answer: C
This line of code loads the scikit-learn model from the specified model URI, allowing you to access its attributes such as feature_importances. Doc: https://mlflow.org/docs/latest/python_api/mlflow.sklearn.html#mlflow.sklearn.load_model
upvoted 1 times
...
random_data_guy
11 months ago
Selected Answer: C
https://mlflow.org/docs/latest/python_api/mlflow.sklearn.html#mlflow.sklearn.load_model
upvoted 1 times
...
trendy01
11 months ago
Selected Answer: C
C. mlflow.sklearn.load_model(model_uri) for two different case, write different code 1. sklean : mlflow.sklearn.load_model(model_uri) 2. xgboost : mlflow.xgboost.load_model(model_uri)
upvoted 2 times
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BokNinja
11 months, 1 week ago
The correct answer is C. mlflow.sklearn.load_model(model_uri)
upvoted 2 times
...

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