Databricks-Machine-Learning-Professional試験無料問題集（62題）「Databricks Certified Machine Learning Professional 認定」

出題：1

Which of the following statements describes streaming with Spark as a model deployment strategy?

A. The inference of batch processed records as soon as a Spark job is run

B. The inference of batch processed records as soon as a trigger is hit

C. The inference of all types of records in real-time

D. The inference of incrementally processed records as soon as trigger is hit

E. The inference of incrementally processed records as soon as a Spark job is run

正解：E 解答を投票する

出題：2

Which of the following describes the concept of MLflow Model flavors?

A. A convention that deployment tools can use to wrap preprocessing logic into a Model

B. A convention that MLflow Model Registry can use to version models

C. A convention that MLflow Model Registry can use to organize its Models by project

D. A convention that MLflow Experiments can use to organize their Runs by project

E. A convention that deployment tools can use to understand the model

正解：D 解答を投票する

出題：3

Which of the following is a benefit of logging a model signature with an MLflow model?

A. The model will be secured by the user that developed it

B. The model will have a unique identifier in the MLflow experiment

C. The model can be deployed using real-time serving tools

D. The schema of input data can be validated when serving models

E. The schema of input data will be converted to match the signature

正解：E 解答を投票する

出題：4

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_STAGE"

C. "MODEL_VERSION_TRANSITIONED_TO_STAGING", "MODEL_VERSION_TRANSITIONED_TO_PRODUCTION"

D. "MODEL_VERSION_CREATED"

E. "MODEL_VERSION_TRANSITIONED_TO_STAGING"

正解：E 解答を投票する

出題：5

A machine learning engineer is manually refreshing a model in an existing machine learning pipeline. The pipeline uses the MLflow Model Registry model "project". The machine learning engineer would like to add a new version of the model to "project".
Which of the following MLflow operations can the machine learning engineer use to accomplish this task?

A. MlflowClient.update_registered_model

B. mlflow.register_model

C. The machine learning engineer needs to create an entirely new MLflow Model Registry model

D. mlflow.add_model_version

E. MlflowClient.get_model_version

正解：A 解答を投票する

出題：6

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 provide the model access to objects like preprocessing models or custom configuration files

C. The context parameter allows the user to provide the model with completely custom if-else logic for the given application's current scenario

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 specify which version of the registered MLflow Model should be used based on the given application's current scenario

正解：E 解答を投票する

Databricks-Machine-Learning-Professional試験無料問題集「Databricks Certified Machine Learning Professional 認定」