Quiz Databricks-Machine-Learning-Professional - Databricks Certified Machine Learning Professional Newest Examcollection Dumps

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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
Certificate Validity Period:2 years
Exam Format:Multiple choice
Related Certifications:Databricks Certified Machine Learning Associate
Exam Duration:120 minutes
Passing Score:70%
Available Languages:English
Real Exam Qty:60
Exam Price:USD 200
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:

TopicDetails
Topic 1
  • Describe model serving deploys and endpoint for every stage
  • Identify scenarios in which feature drift and
  • or label drift are likely to occur
Topic 2
  • 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 3
  • Describe the advantages of using the pyfunc MLflow flavor
  • Manually log parameters, models, and evaluation metrics using MLflow
Topic 4
  • Identify the requirements for tracking nested runs
  • Describe an MLflow flavor and the benefits of using MLflow flavors
Topic 5
  • 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 6
  • Identify JIT feature values as a need for real-time deployment
  • Describe how to list all webhooks and how to delete a webhook
Topic 7
  • 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 (Q47-Q52):

NEW QUESTION # 47
What does an Estimator do in Spark ML?

Answer: A

Explanation:
An Estimator learns from data and produces a Transformer.


NEW QUESTION # 48
Which of the following is a probable response to identifying drift in a machine learning application?

Answer: B


NEW QUESTION # 49
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 is dropping beneath the range of the input variable on which the model was trained.
Which of the following types of drift is present in the above scenario?

Answer: B


NEW QUESTION # 50
A Machine Learning Engineer wants to use on-demand features to train a model. They have a Python UDF, which relies on data fetched from a FeatureLookup. However, in online serving, the pipeline falls when the lookup ID is not found. Which solution will resolve this issue?

Answer: B

Explanation:
When an on-demand feature relies on a FeatureLookup, missing lookup keys can result in None values during online serving. Updating the Python UDF to explicitly handle None and NaN values ensures the feature computation is robust to missing lookups, preventing runtime failures while preserving correct behavior during both training and online inference.


NEW QUESTION # 51
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 one week before the query time. Which feature is a benefit of using a batch serving deployment in this scenario rather than a real-time serving deployment where predictions are computed at query time?

Answer: B


NEW QUESTION # 52
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