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Exam Certified Machine Learning Professional All Questions

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Exam Certified Machine Learning Professional topic 1 question 27 discussion

Actual exam question from Databricks's Certified Machine Learning Professional
Question #: 27
Topic #: 1
[All Certified Machine Learning Professional Questions]

A data scientist has written a function to track the runs of their random forest model. The data scientist is changing the number of trees in the forest across each run.
Which of the following MLflow operations is designed to log single values like the number of trees in a random forest?

  • A. mlflow.log_artifact
  • B. mlflow.log_model
  • C. mlflow.log_metric
  • D. mlflow.log_param
  • E. There is no way to store values like this.
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Suggested Answer: D 🗳️
by BokNinja at Dec. 19, 2023, 2:32 a.m.

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hugodscarvalho
10 months ago
Selected Answer: D
Using mlflow.log_param, the data scientist can easily track and record the number of trees in the random forest model across different runs. Doc: https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.log_param
upvoted 1 times
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random_data_guy
11 months ago
Selected Answer: D
Log a parameter (e.g. model hyperparameter) under the current run. https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.log_param
upvoted 1 times
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trendy01
11 months ago
Selected Answer: D
mlflow.log_param("num_trees", num_trees)
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BokNinja
11 months, 2 weeks ago
import mlflow # Start a new MLflow run with mlflow.start_run(): # Log the parameter mlflow.log_param("num_trees", num_trees)
upvoted 1 times
BokNinja
11 months, 1 week ago
Which makes it D
upvoted 1 times
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