Free PDF Quiz Databricks Databricks-Machine-Learning-Professional Databricks Certified Machine Learning Professional First-grade Valid Exam Duration

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Databricks Databricks-Machine-Learning-Professional Exam Overview:

Certification Vendor:	Databricks
Exam Name:	Databricks Certified Machine Learning Professional
Exam Number:	Databricks-Machine-Learning-Professional
Related Certifications:	Databricks Certified Machine Learning Associate
Real Exam Qty:	60
Certificate Validity Period:	2 years
Available Languages:	English
Exam Price:	USD 200
Exam Duration:	120 minutes
Exam Format:	Multiple choice
Passing Score:	70%
Sample Questions:	Databricks Databricks-Machine-Learning-Professional Sample Questions
Exam Way:	Online (proctored) or Test Center
Pre Condition:	No formal prerequisites, but 1+ years of hands-on experience performing the machine learning tasks outlined in the exam guide is highly recommended. Recommended courses: Machine Learning at Scale and Advanced Machine Learning Operations (instructor-led or self-paced via Databricks Academy).
Official Syllabus URL:	https://www.databricks.com/learn/certification/machine-learning-professional

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

Topic	Details
Topic 1	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 2	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 3	Describe concept drift and its impact on model efficacy Describe summary statistic monitoring as a simple solution for numeric feature drift
Topic 4	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 5	Identify less performant data storage as a solution for other use cases Describe why complex business logic must be handled in streaming deployments
Topic 6	Identify which code block will trigger a shown webhook Describe the basic purpose and user interactions with Model Registry

Databricks Certified Machine Learning Professional Sample Questions (Q18-Q23):

NEW QUESTION # 18
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 the RMSE value with the MLflow run.
They write the following incomplete code block:

Which of the following lines of code can be used to fill in the blank so the code block can successfully complete the task?

A. log_model
B. log_param
C. log_metric
D. There is no way to store values like this.
E. log_artifact

Answer: E

NEW QUESTION # 19
A data scientist wants to examine the data in the Feature Store table table from the database dev as a Spark DataFrame. They have access to Feature Store Client fs. Which line of code can be used to gel the data from table as a Spark DataFrame?

A. fs.create_table("dev.table")
B. fs.get_table("table)
C. fs.read_table("dev.table")
D. fs.get_table("dev.table")

Answer: C

Explanation:
To read data from a Feature Store table as a Spark DataFrame, the correct method is fs.read_table("dev.table"). This retrieves the contents of the table in the dev database using the Feature Store Client (fs) and returns it as a Spark DataFrame.

NEW QUESTION # 20
A machine learning engineer is monitoring categorical input variables for a production machine learning application. The engineer believes that missing values are becoming more prevalent in more recent data for a particular value in one of the categorical input variables. Which of the following tools can the machine learning engineer use to assess their theory?

A. One-way Chi-squared Test
B. Jenson-Shannon distance
C. Two-way Chi-squared Test
D. None of these
E. Kolmogorov-Smirnov (KS) test

Answer: A

NEW QUESTION # 21
A machine learning engineer is monitoring label values for a production machine learning classification model. The engineer believes that the relative prevalence of the classes is becoming changing in more recent data. Which tool can the machine learning engineer use to assess their theory?

A. One-way Chi-squared Test
B. Jenson-Shannon distance
C. Two-way Chi-squared Test
D. Kolmogorov-Smirnov (KS) test

Answer: A

Explanation:
A One-way Chi-squared Test is used to compare observed class distributions with expected distributions to determine if there has been a significant shift. This makes it suitable for detecting label drift in classification tasks, where the relative prevalence of classes may be changing over time.

NEW QUESTION # 22
Which is a benefit of logging an input example with an MLflow model?

A. The model evaluation metrics are stored with the model
B. An example record is available to test serving applications
C. The environment requirements are packaged with the MLmodel file
D. An example prediction is available to test post-inference pipelines

Answer: B

Explanation:
Logging an input example with an MLflow model provides a concrete sample of the data format expected by the model. This helps serving applications and users understand the model's input structure and verify that inference requests are properly formatted when deploying or testing the model in production.

NEW QUESTION # 23
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