This page was exported from Top Exam Collection [ http://blog.topexamcollection.com ] Export date:Thu Apr 3 11:37:07 2025 / +0000 GMT ___________________________________________________ Title: Jun-2024 Pass Your Databricks-Machine-Learning-Professional Exam at the First Try with 100% Real Exam [Q15-Q34] --------------------------------------------------- Jun-2024 Pass Your Databricks-Machine-Learning-Professional Exam at the First Try with 100% Real Exam Get Real Exam Questions for Databricks-Machine-Learning-Professional with New Questions Databricks Databricks-Machine-Learning-Professional Exam Syllabus Topics: TopicDetailsTopic 1Test whether the updated model performs better on the more recent data Identify when retraining and deploying an updated model is a probable solution to driftTopic 2Describe concept drift and its impact on model efficacy Describe summary statistic monitoring as a simple solution for numeric feature driftTopic 3Identify that data can arrive out-of-order with structured streaming Identify how model serving uses one all-purpose cluster for a model deploymentTopic 4Identify a use case for HTTP webhooks and where the Webhook URL needs to come Identify advantages of using Job clusters over all-purpose clustersTopic 5Create, overwrite, merge, and read Feature Store tables in machine learning workflows View Delta table history and load a previous version of a Delta tableTopic 6Identify which code block will trigger a shown webhook Describe the basic purpose and user interactions with Model RegistryTopic 7Describe the advantages of using the pyfunc MLflow flavor Manually log parameters, models, and evaluation metrics using MLflowTopic 8Identify less performant data storage as a solution for other use cases Describe why complex business logic must be handled in streaming deployments   NEW QUESTION 15A 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?           NEW QUESTION 16A 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 in each of the stages in the MLflow Model Registry. The engineer wants to know which model versions can be queried once Model Serving is enabled for the model.Which of the following lists all of the MLflow Model Registry stages whose model versions are automatically deployed with Model Serving?  Staging. Production. Archived  Production  None. Staging. Production. Archived  Staging. Production  [None. Staging. Production NEW QUESTION 17A 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 MLflow Model Registry.Which of the following model URIs can be used to query the described model version?  https://<databricks-instance>/model-serving/recommender/Production/invocations  The version number of the model version in Production is necessary to complete this task.  https://<databricks-instance>/model/recommender/stage-production/invocations  https://<databricks-instance>/model-serving/recommender/stage-production/invocations  https://<databricks-instance>/model/recommender/Production/invocations NEW QUESTION 18Which of the following is a probable response to identifying drift in a machine learning application?  All of these responses  Sunsetting the machine learning application  Rebuilding the machine learning application with a new label variable  Retraining and deploying a model on more recent data  None of these responses NEW QUESTION 19A 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?  Edge/on-device  Streaming  None of these strategies will meet the requirements.  Batch  Real-time NEW QUESTION 20Which of the following statements describes streaming with Spark as a model deployment strategy?  The inference of batch processed records as soon as a trigger is hit  The inference of all types of records in real-time  The inference of batch processed records as soon as a Spark job is run  The inference of incrementally processed records as soon as trigger is hit  The inference of incrementally processed records as soon as a Spark job is run NEW QUESTION 21A 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 of the model so they can document what type of data is expected as input.Which of the following MLflow operations can be used to perform this task?  mlflow.models.schema.infer_schema  mlflow.models.signature.infer_signature  mlflow.models.Model.get_input_schema  mlflow.models.Model.signature  There is no way to obtain the input schema and the output schema of an unlogged model. NEW QUESTION 22A 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 manage nested Hyperopt runs with MLflow Autologging.Which of the following approaches will create a single parent run for the process and a child run for each unique combination of hyperparameter values when using Hyperopt and MLflow Autologging?  Startinq a manual parent run before calling fmin  Ensuring that a built-in model flavor is used for the model logging  Starting a manual child run within the objective function  There is no way to accomplish nested runs with MLflow Autoloqqinq and Hyperopt  MLflow Autoloqqinq will automatically accomplish this task with Hyperopt NEW QUESTION 23A machine learning engineer has developed a random forest model using scikit-learn, logged the model using MLflow as random_forest_model, and stored its run ID in the run_id Python variable. They now want to deploy that model by performing batch inference on a Spark DataFrame spark_df.Which of the following code blocks can they use to create a function called predict that they can use to complete the task?    It is not possible to deploy a scikit-learn model on a Spark DataFrame.       NEW QUESTION 24Which of the following tools can assist in real-time deployments by packaging software with its own application, tools, and libraries?  Cloud-based compute  None of these tools  REST APIs  Containers  Autoscaling clusters NEW QUESTION 25A 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.  Option A  Option B  Option C  Option D  Option E NEW QUESTION 26A 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?           NEW QUESTION 27A 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 and made ready for inference in a series of equal-sized batches.Which of the following tools can be used to provide this type of continuous processing?  Spark UDFs  [Structured Streaming  MLflowD Delta Lake  AutoML NEW QUESTION 28A 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 when the inference table is a stream source?  Replace “inference” with the path to the location of the Delta table  Replace schema(schema) with option(“maxFilesPerTriqqer”, 1}  Replace spark.read with spark.readStream  Replace formatfdelta”) with format(“stream”)  Replace predict with a stream-friendly prediction function NEW QUESTION 29A 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?  The pvfunc model can be used to deploy models in a parallelizable fashion  The same preprocessing logic will automatically be applied when calling fit  The same preprocessing logic will automatically be applied when calling predict  This approach has no impact when loading the logged Pvfunc model for downstream deployment  There is no longer a need for pipeline-like machine learning objects NEW QUESTION 30A 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?  mlflow.log_artifact  mlflow.log_model  mlflow.log_metric  mlflow.log_param  There is no way to store values like this. NEW QUESTION 31A 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?  mlflow.register_model(model_uri, “best_model”)  mlflow.register_model(run_id, “best_model”)  mlflow.register_model(f”runs:/{run_id}/best_model”, “model”)  mlflow.register_model(model_uri, “model”)  mlflow.register_model(f”runs:/{run_id}/model”) NEW QUESTION 32Which of the following describes concept drift?  Concept drift is when there is a change in the distribution of an input variable  Concept drift is when there is a change in the distribution of a target variable  Concept drift is when there is a change in the relationship between input variables and target variables  Concept drift is when there is a change in the distribution of the predicted target given by the model  None of these describe Concept drift NEW QUESTION 33Which of the following MLflow operations can be used to automatically calculate and log a Shapley feature importance plot?  mlflow.shap.log_explanation  None of these operations can accomplish the task.  mlflow.shap  mlflow.log_figure  client.log_artifact NEW QUESTION 34Which of the following is an advantage of using the python_function(pyfunc) model flavor over the built-in library-specific model flavors?  python_function provides no benefits over the built-in library-specific model flavors  python_function can be used to deploy models in a parallelizable fashion  python_function can be used to deploy models without worrying about which library was used to create the model  python_function can be used to store models in an MLmodel file  python_function can be used to deploy models without worrying about whether they are deployed in batch, streaming, or real-time environments  Loading … Updated Databricks-Machine-Learning-Professional Certification Exam Sample Questions: https://www.topexamcollection.com/Databricks-Machine-Learning-Professional-vce-collection.html --------------------------------------------------- Images: https://blog.topexamcollection.com/wp-content/plugins/watu/loading.gif https://blog.topexamcollection.com/wp-content/plugins/watu/loading.gif --------------------------------------------------- --------------------------------------------------- Post date: 2024-06-07 13:48:01 Post date GMT: 2024-06-07 13:48:01 Post modified date: 2024-06-07 13:48:01 Post modified date GMT: 2024-06-07 13:48:01