Valid Databricks-Machine-Learning-Professional Study Notes, Databricks-Machine-Learning-Professional Well Prep

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Databricks Databricks-Machine-Learning-Professional Exam Syllabus Topics:

Section	Weight	Objectives
Model Deployment	12%	- Custom model serving - Deployment strategies - Model rollout and version management
ML Ops	44%	- Environment management with Databricks Asset Bundles - Model monitoring and drift detection with Lakehouse Monitoring - Automated retraining workflows - Testing and validation strategies
Model Development	44%	- Distributed training and hyperparameter tuning - Advanced MLflow usage - Feature Store and automated feature pipelines - Scalable ML pipelines with SparkML

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Databricks Certified Machine Learning Professional Sample Questions (Q126-Q131):

NEW QUESTION # 126
Which MLflow function registers a model to the registry?

A. mlflow.deploy_model()
B. mlflow.register_model()
C. mlflow.log_param()
D. mlflow.create_model()

Answer: B

Explanation:
mlflow.register_model() promotes a model into the Model Registry.

NEW QUESTION # 127
Which statement describes streaming with Spark as a model deployment strategy?

A. The inference of incrementally processed records as soon as trigger is hit
B. The inference of all types of records in real-time
C. The inference of batch processed records as soon as a trigger is hit
D. The inference of incrementally processed records as soon as a Spark job is run
E. The inference of batch processed records as soon as a Spark job is run

Answer: D

NEW QUESTION # 128
A data scientist set up a machine learning pipeline to automatically log feature importance data from a CSV with each run. They now want to view the feature importance data in Databricks.
Which location in Databricks will show this data?

A. The Artifacts section of the MLflow Experiment page
B. The Data section of the MLflow Run page/span>
C. The Artifacts section of the MLflow Run page
D. The MLflow Model Registry Model page

Answer: C

Explanation:
When a data scientist logs feature importance data (e.g., as a CSV or JSON file) using MLflow, it is stored as an artifact of that specific run. These artifacts are visible under the Artifacts section of the MLflow Run page in Databricks, where users can view or download the logged files associated with that particular experiment run.

NEW QUESTION # 129
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 provide the model with completely custom if-else logic for the given application's current scenario
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 include relevant details of the business case to allow downstream users to understand the purpose of the model
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

Answer: E

NEW QUESTION # 130
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 to have one parent run for the tuning process with a child run for each unique combination of hyperparameter values.
They are using the following code block:

The code block is not nesting the runs in MLflow as they expected.
Which of the following changes does the data scientist need to make to the above code block so that it successfully nests the child runs under the parent run in MLflow?

A. Add the nested=True argument to the parent run
B. Indent the child run blocks within the parent run block
C. Provide the same name to the run name parameter for all three run blocks
D. Remove the nested=True argument from the child runs
E. Add the nested=True argument to the parent run and remove the nested=True arguments from the child runs

Answer: E

NEW QUESTION # 131
......

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