Databricks-Machine-Learning-Professional 무료 덤프문제 온라인 액세스

A data scientist has developed a scikit-learn random forest model model, but they have not yet logged model with MLflow. They want to obtain the input schema and the output schema of the model so they can document what type of data is expected as input.
Which of the following MLflow operations can be used to perform this task?

• A.There is no way to obtain the input schema and the output schema of an unlogged model.
• B.mlflow.models.signature.infer_signature
• C.mlflow.models.Model.signature
• D.mlflow.models.Model.get_input_schema
• E.mlflow.models.schema.infer_schema

Which of the following is a probable response to identifying drift in a machine learning application?

• A.Sunsetting the machine learning application
• B.None of these responses
• C.All of these responses
• D.Retraining and deploying a model on more recent data
• E.Rebuilding the machine learning application with a new label variable

A data scientist has developed a scikit-learn model sklearn_model and they want to log the model using MLflow.
They write the following incomplete code block:

Which of the following lines of code can be used to fill in the blank so the code block can successfully complete the task?

• A.mlflow.sklearn.load_model("model")
• B.mlflow.sklearn.log_model(sklearn_model, "model")
• C.mlflow.spark.log_model(sklearn_model, "model")
• D.mlflow.sklearn.track_model(sklearn_model, "model")
• E.mlflow.spark.track_model(sklearn_model, "model")

In a continuous integration, continuous deployment (CI/CD) process for machine learning pipelines, which of the following events commonly triggers the execution of automated testing?

• A.The arrival of a new feature table in the Feature Store
• B.CI/CD pipelines are not needed for machine learning pipelines
• C.The launch of a new cost-efficient SQL endpoint
• D.The arrival of a new model version in the MLflow Model Registry
• E.The launch of a new cost-efficient job cluster

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_model
• B.mlflow.log_param
• C.There is no way to store values like this.
• D.mlflow.log_metric
• E.mlflow.log_artifact