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

Topic	Details
Topic 1	Identify a use case for HTTP webhooks and where the Webhook URL needs to come Identify advantages of using Job clusters over all-purpose clusters
Topic 2	Identify JIT feature values as a need for real-time deployment Describe how to list all webhooks and how to delete a webhook
Topic 3	Describe the advantages of using the pyfunc MLflow flavor Manually log parameters, models, and evaluation metrics using MLflow
Topic 4	Describe model serving deploys and endpoint for every stage Identify scenarios in which feature drift and or label drift are likely to occur
Topic 5	Create, overwrite, merge, and read Feature Store tables in machine learning workflows View Delta table history and load a previous version of a Delta table
Topic 6	Describe concept drift and its impact on model efficacy Describe summary statistic monitoring as a simple solution for numeric feature drift
Topic 7	Test whether the updated model performs better on the more recent data Identify when retraining and deploying an updated model is a probable solution to drift
Topic 8	Identify that data can arrive out-of-order with structured streaming Identify how model serving uses one all-purpose cluster for a model deployment
Topic 9	Identify less performant data storage as a solution for other use cases Describe why complex business logic must be handled in streaming deployments
Topic 10	Identify live serving benefits of querying precomputed batch predictions Describe Structured Streaming as a common processing tool for ETL pipelines

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Databricks Certified Machine Learning Professional Sample Questions (Q42-Q47):

NEW QUESTION # 42
A machine learning engineer wants to load the data from the very first version of a Delta table from location path. Which of the following lines of code can be used to accomplish this task?

A. spark.read.format("delta").option("version", 0).load(path)
B. spark.read.format("delta").option("versionAsOf", 0).load(path)
C. spark.read.format("delta").option("versionAsOf", 1).load(path)
D. spark.read.format("delta").option("version", 1).load(path)

Answer: C

Explanation:
In Delta Lake, the option("versionAsOf", <version_number>) parameter is used to load a specific version of a Delta table.
Since Delta table versions are 1-indexed (the first version is version 1), using .option("versionAsOf", 1) correctly loads the very first version of the table.

NEW QUESTION # 43
Which of the following is a probable response to identifying drift in a machine learning application?

A. None of these responses
B. Rebuilding the machine learning application with a new label variable
C. All of these responses
D. Retraining and deploying a model on more recent data
E. Sunsetting the machine learning application

Answer: A

NEW QUESTION # 44
Which MLflow component is used to log parameters, metrics, and artifacts during model training?

A. MLflow Projects
B. Model Registry
C. MLflow Tracking
D. MLflow Models

Answer: C

Explanation:
MLflow Tracking records experiment runs including:
parameters
metrics
artifacts (models, plots, etc.)

NEW QUESTION # 45
Which of the following statements describes streaming with Spark as a model deployment strategy?

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

Answer: B

NEW QUESTION # 46
Which of the following describes the concept of MLflow Model flavors?

A. A convention that deployment tools can use to wrap preprocessing logic into a Model
B. A convention that deployment tools can use to understand the model
C. A convention that MLflow Model Registry can use to organize its Models by project
D. A convention that MLflow Model Registry can use to version models
E. A convention that MLflow Experiments can use to organize their Runs by project

Answer: E

NEW QUESTION # 47
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