[2024年更新]合格できるDatabricks Databricks-Machine-Learning-Professionalプレミアム資料テストエンジンPDFの無料問題集お試しセット
2024年最新のリアルDatabricks-Machine-Learning-Professional問題集テストエンジン試験問題はここにある
質問 # 11
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_param
- B. There is no way to store values like this.
- C. mlflow.log_model
- D. mlflow.log_artifact
- E. mlflow.log_metric
正解：E
質問 # 12
A data scientist has created a Python function compute_features that returns a Spark DataFrame with the following schema:
The resulting DataFrame is assigned to the features_df variable. The data scientist wants to create a Feature Store table using features_df.
Which of the following code blocks can they use to create and populate the Feature Store table using the Feature Store Client fs?
- A.
- B.
- C. features_df.write.mode("feature").path("new_table")
- D. features_df.write.mode("fs").path("new_table")
- E.
正解：B
質問 # 13
A machine learning engineer is migrating a machine learning pipeline to use Databricks Machine Learning. They have programmatically identified the best run from an MLflow Experiment and stored its URI in the model_uri variable and its Run ID in the run_id variable. They have also determined that the model was logged with the name "model". Now, the machine learning engineer wants to register that model in the MLflow Model Registry with the name "best_model".
Which of the following lines of code can they use to register the model to the MLflow Model Registry?
- A. mlflow.register_model(model_uri, "best_model")
- B. mlflow.register_model(f"runs:/{run_id}/best_model", "model")
- C. mlflow.register_model(f"runs:/{run_id}/model")
- D. mlflow.register_model(model_uri, "model")
- E. mlflow.register_model(run_id, "best_model")
正解：D
質問 # 14
Which of the following describes the purpose of the context parameter in the predict method of Python models for MLflow?
- A. The context parameter allows the user to include relevant details of the business case to allow downstream users to understand the purpose of the model
- B. The context parameter allows the user to specify which version of the registered MLflow Model should be used based on the given application's current scenario
- C. The context parameter allows the user to provide the model access to objects like preprocessing models or custom configuration files
- D. The context parameter allows the user to document the performance of a model after it has been deployed
- E. The context parameter allows the user to provide the model with completely custom if-else logic for the given application's current scenario
正解：B
質問 # 15
A machine learning engineer has registered a sklearn model in the MLflow Model Registry using the sklearn model flavor with UI model_uri.
Which of the following operations can be used to load the model as an sklearn object for batch deployment?
- A. mlflow.sklearn.read_model(model_uri)
- B. mlflow.spark.load_model(model_uri)
- C. mlflow.pyfunc.read_model(model_uri)
- D. mlflow.sklearn.load_model(model_uri)
- E. mlflow.pyfunc.load_model(model_uri)
正解：E
質問 # 16
A machine learning engineer wants to log feature importance data from a CSV file at path importance_path with an MLflow run for model model.
Which of the following code blocks will accomplish this task inside of an existing MLflow run block?
A)
B)
C) mlflow.log_data(importance_path, "feature-importance.csv")
D) mlflow.log_artifact(importance_path, "feature-importance.csv")
E) None of these code blocks tan accomplish the task.
- A. Option A
- B. Option B
- C. Option C
- D. Option D
- E. Option E
正解：A
質問 # 17
Which of the following is a simple statistic to monitor for categorical feature drift?
- A. Percentage of missing values
- B. Mode, number of unique values, and percentage of missing values
- C. Number of unique values
- D. Mode
- E. None of these
正解：B
質問 # 18
A data scientist would like to enable MLflow Autologging for all machine learning libraries used in a notebook. They want to ensure that MLflow Autologging is used no matter what version of the Databricks Runtime for Machine Learning is used to run the notebook and no matter what workspace-wide configurations are selected in the Admin Console.
Which of the following lines of code can they use to accomplish this task?
- A. mlflow.spark.autolog()
- B. spark.conf.set("autologging", True)
- C. mlflow.autolog()
- D. mlflow.sklearn.autolog()
- E. It is not possible to automatically log MLflow runs.
正解：B
質問 # 19
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 launch of a new cost-efficient SQL endpoint
- B. The arrival of a new feature table in the Feature Store
- C. The launch of a new cost-efficient job cluster
- D. CI/CD pipelines are not needed for machine learning pipelines
- E. The arrival of a new model version in the MLflow Model Registry
正解：C
質問 # 20
A machine learning engineer is monitoring categorical input variables for a production machine learning application. The engineer believes that missing values are becoming more prevalent in more recent data for a particular value in one of the categorical input variables.
Which of the following tools can the machine learning engineer use to assess their theory?
- A. One-way Chi-squared Test
- B. Two-way Chi-squared Test
- C. Kolmogorov-Smirnov (KS) test
- D. None of these
- E. Jenson-Shannon distance
正解：A
質問 # 21
A machine learning engineer is attempting to create a webhook that will trigger a Databricks Job job_id when a model version for model model transitions into any MLflow Model Registry stage.
They have the following incomplete code block:
Which of the following lines of code can be used to fill in the blank so that the code block accomplishes the task?
- A. "MODEL_VERSION_TRANSITIONED_TO_PRODUCTION"
- B. "MODEL_VERSION_TRANSITIONED_TO_STAGING", "MODEL_VERSION_TRANSITIONED_TO_PRODUCTION"
- C. "MODEL_VERSION_TRANSITIONED_TO_STAGING"
- D. "MODEL_VERSION_TRANSITIONED_STAGE"
- E. "MODEL_VERSION_CREATED"
正解：C
質問 # 22
A machine learning engineer has created a webhook with the following code block:
Which of the following code blocks will trigger this webhook to run the associate job?
- A.
- B.
- C.
- D.
- E.
正解：D
質問 # 23
A machine learning engineer needs to select a deployment strategy for a new machine learning application. The feature values are not available until the time of delivery, and results are needed exceedingly fast for one record at a time.
Which of the following deployment strategies can be used to meet these requirements?
- A. Batch
- B. Edge/on-device
- C. None of these strategies will meet the requirements.
- D. Real-time
- E. Streaming
正解：D
質問 # 24
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.spark.track_model(sklearn_model, "model")
- B. mlflow.sklearn.track_model(sklearn_model, "model")
- C. mlflow.sklearn.log_model(sklearn_model, "model")
- D. mlflow.sklearn.load_model("model")
- E. mlflow.spark.log_model(sklearn_model, "model")
正解：A
質問 # 25
Which of the following describes concept drift?
- A. Concept drift is when there is a change in the distribution of a target variable
- B. Concept drift is when there is a change in the distribution of an input variable
- C. Concept drift is when there is a change in the relationship between input variables and target variables
- D. None of these describe Concept drift
- E. Concept drift is when there is a change in the distribution of the predicted target given by the model
正解：E
質問 # 26
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