CERTIFIED-MACHINE-LEARNING-PROFESSIONAL Exam Questions

A data scientist has developed a model model and computed the RMSE of the model on the test set. They have assigned this value to the variable rmse. They now want to manually store...

Which of the following MLflow operations can be used to automatically calculate and log a Shapley feature importance plot?

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...

A machine learning engineer and data scientist are working together to convert a batch deployment to an always-on streaming deployment. The machine learning engineer has expressed...

Which of the following deployment paradigms can centrally compute predictions for a single record with exceedingly fast results?

A machine learning engineering team wants to build a continuous pipeline for data preparation of a machine learning application. The team would like the data to be fully processed...

A machine learning engineer wants to deploy a model for real-time serving using MLflow Model Serving. For the model, the machine learning engineer currently has one model version i...

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 t...

A machine learning engineer is converting a Hyperopt-based hyperparameter tuning process from manual MLflow logging to MLflow Autologging. They are trying to determine how to manag...

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

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

A machine learning engineer has deployed a model recommender using MLflow Model Serving. They now want to query the version of that model that is in the Production stage of the MLf...

Which of the following tools can assist in real-time deployments by packaging software with its own application, tools, and libraries?

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 u...

A data scientist set up a machine learning pipeline to automatically log a data visualization with each run. They now want to view the visualizations in Databricks. Which of the fo...

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 followin...

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

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

A machine learning engineering team has written predictions computed in a batch job to a Delta table for querying. However, the team has noticed that the querying is running slowly...

A machine learning engineer needs to deliver predictions of a machine learning model in real- time. However, the feature values needed for computing the predictions are available o...

Which of the following describes the purpose of the context parameter in the predict method of Python models for MLflow?

A machine learning engineer has developed a model and registered it using the FeatureStoreClient fs. The model has model URI model_uri. The engineer now needs to perform batch infe...

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 resul...

A machine learning engineer is using the following code block as part of a batch deployment pipeline: Which of the following changes needs to be made so this code block will work w...

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 Experimen...

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 learni...

Which of the following is an advantage of using the python_function(pyfunc) model flavor over the built-in library-specific model flavors?

Which of the following lists all of the model stages are available in the MLflow Model Registry?

Which of the following MLflow operations can be used to delete a model from the MLflow Model Registry?

A machine learning engineer wants to programmatically create a new Databricks Job whose schedule depends on the result of some automated tests in a machine learning pipeline. Which...

A machine learning engineer wants to view all of the active MLflow Model Registry Webhooks for a specific model. They are using the following code block: Which of the following cha...

Which of the following describes concept drift?

A machine learning engineer is monitoring categorical input variables for a production machine learning application. The engineer believes that missing values are becoming more pre...

A data scientist is using MLflow to track their machine learning experiment. As a part of each MLflow run, they are performing hyperparameter tuning. The data scientist would like...

Which of the following is a simple, low-cost method of monitoring numeric feature drift?

A data scientist has developed a model to predict ice cream sales using the expected temperature and expected number of hours of sun in the day. However, the expected temperature i...

A data scientist wants to remove the star_rating column from the Delta table at the location path. To do this, they need to load in data and drop the star_rating column. Which of t...

Which of the following operations in Feature Store Client fs can be used to return a Spark DataFrame of a data set associated with a Feature Store table?

A machine learning engineer is in the process of implementing a concept drift monitoring solution. They are planning to use the following steps: 1. Deploy a model to production and...

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 data scientist is utilizing MLflow to track their machine learning experiments. After completing a series of runs for the experiment with experiment ID exp_id, the data scientist...

Which of the following MLflow Model Registry use cases requires the use of an HTTP Webhook?

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 fitti...

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 st...

Which of the following Databricks-managed MLflow capabilities is a centralized model store?

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 Regis...

A data scientist has developed and logged a scikit-learn random forest model model, and then they ended their Spark session and terminated their cluster. After starting a new clust...

Which of the following is a simple statistic to monitor for categorical feature drift?

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

After a data scientist noticed that a column was missing from a production feature set stored as a Delta table, the machine learning engineering team has been tasked with determini...