최신Databricks Certified Machine Learning Professional - Databricks-Machine-Learning-Professional무료샘플문제
문제1
Which of the following MLflow operations can be used to delete a model from the MLflow Model Registry?
Which of the following MLflow operations can be used to delete a model from the MLflow Model Registry?
정답: D
문제2
A data scientist has computed updated feature values for all primary key values stored in the Feature Store table features. In addition, feature values for some new primary key values have also been computed. The updated feature values are stored in the DataFrame features_df. They want to replace all data in features with the newly computed data. Which of the following code blocks can they use to perform this task using the Feature Store Client fs?
A data scientist has computed updated feature values for all primary key values stored in the Feature Store table features. In addition, feature values for some new primary key values have also been computed. The updated feature values are stored in the DataFrame features_df. They want to replace all data in features with the newly computed data. Which of the following code blocks can they use to perform this task using the Feature Store Client fs?
정답: D
문제3
A Data Scientist is tasked with developing models to forecast product demand. The company offers 5000 different product types, and the Data Scientist must generate weekly forecasts for each type. They have access to two years of historical purchase data and are given ample project budget.
For their next project, they want to build 5000 separate Random Forest models, one for each product type. They aim to train all the models as quickly as possible with minimal setup.
Which approach meets these requirements?
A Data Scientist is tasked with developing models to forecast product demand. The company offers 5000 different product types, and the Data Scientist must generate weekly forecasts for each type. They have access to two years of historical purchase data and are given ample project budget.
For their next project, they want to build 5000 separate Random Forest models, one for each product type. They aim to train all the models as quickly as possible with minimal setup.
Which approach meets these requirements?
정답: D
설명: (KoreaDumps 회원만 볼 수 있음)
문제4
Which of the following is an obstacle related to streaming machine learning applications?
Which of the following is an obstacle related to streaming machine learning applications?
정답: B
설명: (KoreaDumps 회원만 볼 수 있음)
문제5
A Data Scientist at an online gaming company is creating a model to predict player churn. The company currently collects terabytes of player activity logs daily, which are stored in Databricks and processed for daily reporting. The Data Scientist has completed feature engineering and the resulting data is saved as a Delta Table with a size of 500GB. They need to next build the model for the most performant and cost-effective performance for Databricks. Which approach will do this?
A Data Scientist at an online gaming company is creating a model to predict player churn. The company currently collects terabytes of player activity logs daily, which are stored in Databricks and processed for daily reporting. The Data Scientist has completed feature engineering and the resulting data is saved as a Delta Table with a size of 500GB. They need to next build the model for the most performant and cost-effective performance for Databricks. Which approach will do this?
정답: C
설명: (KoreaDumps 회원만 볼 수 있음)
문제6
A machine learning engineer is in the process of implementing a feature drift monitoring solution.
They are planning to use the following steps:
1. Measure the distributions of each feature variable in the training
set
2. Deploy a model to production
3. Measure the distributions of each feature variable in inference
4. _______
Which action should be completed as Step #4?
A machine learning engineer is in the process of implementing a feature drift monitoring solution.
They are planning to use the following steps:
1. Measure the distributions of each feature variable in the training
set
2. Deploy a model to production
3. Measure the distributions of each feature variable in inference
4. _______
Which action should be completed as Step #4?
정답: D
설명: (KoreaDumps 회원만 볼 수 있음)
문제7
A Machine Learning Engineer wants to implement MLOps. They currently have three environments: dev, stage, and prod. They have many private PyPI packages that they use to train their models, and they are concerned that their environments will not be consistent between dev, stage, and prod. The engineer needs to follow enterprise scaling and CI/CD best practices to ensure that their environments are consistent. Which approach will do this?
A Machine Learning Engineer wants to implement MLOps. They currently have three environments: dev, stage, and prod. They have many private PyPI packages that they use to train their models, and they are concerned that their environments will not be consistent between dev, stage, and prod. The engineer needs to follow enterprise scaling and CI/CD best practices to ensure that their environments are consistent. Which approach will do this?
정답: C
설명: (KoreaDumps 회원만 볼 수 있음)
문제8
A Machine Learning Engineer is implementing integration tests for an ML pipeline in Databricks.
The current integration test runs the complete workflow but takes four hours to execute due to large dataset processing and extensive model training. They need to select an approach that will be the most effective for optimizing integration test execution while maintaining test reliability. The approach should also be based on MLOps best practices. Which approach will do this?
A Machine Learning Engineer is implementing integration tests for an ML pipeline in Databricks.
The current integration test runs the complete workflow but takes four hours to execute due to large dataset processing and extensive model training. They need to select an approach that will be the most effective for optimizing integration test execution while maintaining test reliability. The approach should also be based on MLOps best practices. Which approach will do this?
정답: B
설명: (KoreaDumps 회원만 볼 수 있음)
문제9
A data scientist wants to track the runs of their random forest model. The data scientist is changing the number of trees and the maximum depth of the trees in the forest across each run.
They write the following code block:
Which Python object type does params need to be an instance of?
A data scientist wants to track the runs of their random forest model. The data scientist is changing the number of trees and the maximum depth of the trees in the forest across each run.
They write the following code block:
Which Python object type does params need to be an instance of?
정답: B
설명: (KoreaDumps 회원만 볼 수 있음)
문제10
Why are Delta tables often used to store machine learning features?
Why are Delta tables often used to store machine learning features?
정답: C
설명: (KoreaDumps 회원만 볼 수 있음)
문제11
What is the main purpose of the Databricks Feature Store?
What is the main purpose of the Databricks Feature Store?
정답: A
설명: (KoreaDumps 회원만 볼 수 있음)
문제12
Which of the following statements about built-in library-specific MLflow Model flavors is true?
Which of the following statements about built-in library-specific MLflow Model flavors is true?
정답: B
설명: (KoreaDumps 회원만 볼 수 있음)
문제13
A Machine Learning Engineer is using joblibspark and MLflowCallback to perform a distributed hyperparameter tuning experiment via Optuna. Assuming they have a single objective they are optimizing for, what will be the default sampler implemented by Optuna?
A Machine Learning Engineer is using joblibspark and MLflowCallback to perform a distributed hyperparameter tuning experiment via Optuna. Assuming they have a single objective they are optimizing for, what will be the default sampler implemented by Optuna?
정답: D
설명: (KoreaDumps 회원만 볼 수 있음)