최신 Databricks-Machine-Learning-Professional 무료덤프 - Databricks Certified Machine Learning Professional

문제1

A machine learning engineer wants to log and deploy a model as an MLflow pyfunc model. They have custom preprocessing that needs to be completed on feature variables prior to fitting the model or computing predictions using that model. They decide to wrap this preprocessing in a custom model class ModelWithPreprocess, where the preprocessing is performed when calling fit and when calling predict. They then log the fitted model of the ModelWithPreprocess class as a pyfunc model.
Which of the following is a benefit of this approach when loading the logged pyfunc model for downstream deployment?

A. The pvfunc model can be used to deploy models in a parallelizable fashion

B. The same preprocessing logic will automatically be applied when calling predict

C. The same preprocessing logic will automatically be applied when calling fit

D. There is no longer a need for pipeline-like machine learning objects

E. This approach has no impact when loading the logged Pvfunc model for downstream deployment

정답: D

문제2

Which of the following is a reason for using Jensen-Shannon (JS) distance over a Kolmogorov-Smirnov (KS) test for numeric feature drift detection?

A. JS is more robust when working with large datasets

B. None of these reasons

C. JS is not normalized or smoothed

D. JS does not require any manual threshold or cutoff determinations

E. All of these reasons

정답: A

문제3

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.get_model_version

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.update_registered_model

정답: E

문제4

A machine learning engineering manager has asked all of the engineers on their team to add text descriptions to each of the model projects in the MLflow Model Registry. They are starting with the model project "model" and they'd like to add the text in the model_description variable.
The team is using the following line of code:

Which of the following changes does the team need to make to the above code block to accomplish the task?

A. There no changes necessary

B. Replace update_registered_model with update_model_version

C. Add a Python model as an argument to update_registered_model

D. Replace client.update_registered_model with mlflow

E. Replace description with artifact

정답: A

문제5

A machine learning engineer wants to move their model version model_version for the MLflow Model Registry model model from the Staging stage to the Production stage using MLflow Client client.
Which of the following code blocks can they use to accomplish the task?

A.

B.

C.

D.

E.

정답: E

문제6

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

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

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

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

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

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

정답: B

최신 Databricks-Machine-Learning-Professional 무료덤프 - Databricks Certified Machine Learning Professional

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