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Databricks ML Professional Exam:
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Professional exam? Get complete syllabus details by
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ML Professional
Exam Format
Exam Name: Databricks Certified Machine
Learning Professional
Exam Code: Machine Learning Professional
Duration: 120 mins
Number of Questions: 60
Passing Score: 70%
Practice Exams: Databricks Machine
Learning Professional Certification Practice
Exam
Recommended Training: Machine Learning
in Production
Databricks Machine
Learning
Professional
Get a glimpse of the actual
exam questions with the
help of these sample
questions.
Q1. A data scientist has developed a model to predict whether or not it will rain
using the expected temperature and expected cloud coverage.
However, the relationship between expected temperature and whether or not it
rains has changed dramatically since the time period of the data on which the
model was trained.
Which type of drift is present in the above scenario?
Options:
a) Label drift
b) Feature drift
c) Concept drift
d) Prediction drift
e) None of these
Answer:
c) Concept drift
Q2. A data scientist has made the suggestion that their team starts using Feature
Store in Databricks Machine Learning. The data scientist claims that using Feature
Store will meet a number of their feature management needs.
Which of the following will the team need to implement because it is not
automatically provided by Feature Store?
Options:
a) Share features across workspaces
b) Measure the drift for individual features
c) Discover features used throughout the organization
d) Track where specific feature tables are used
e) Monitor the freshness of feature tables
Answer:
b) Measure the drift for individual features
Q3. A data scientist has developed and logged a scikit-learn gradient boosting
regressor model model, and then they ended their Spark session and terminated
their cluster.
After starting a new cluster, they want to review the estimators_ of the original
model object to analyze each of the trees in the trained model.
Which line of code can be used to restore the model object so that estimators_ is
available?
Options:
a) mlflow.sklearn.load_model(model_uri)
b) client.pyfunc.load_model(model_uri)
c) mlflow.load_model(model_uri)
d) client.list_artifacts(run_id)["estimators.csv"]
e) This can only be viewed in the MLflow Experiments UI
Answer:
a) mlflow.sklearn.load_model(model_uri)
Q4. When merging data into a Delta table, which clause are essential to specify the
conditions under which a row should be updated or inserted?
Options:
a) WHEN MATCHED THEN
b) ON DUPLICATE KEY UPDATE
c) IF EXISTS THEN UPDATE ELSE INSERT
d) ON CONFLICT DO UPDATE
Answer:
a) WHEN MATCHED THEN
d) ON CONFLICT DO UPDATE
Q5. For Advanced Experiment Tracking, which of the following are true about
model signatures in MLflow?
Options:
a) They are optional but recommended
b) They define the input and output schema of the model
c) They must be manually updated with each experiment run
d) They are automatically generated for all models
Answer:
a) They are optional but recommended
b) They define the input and output schema of the model
Do Databricks Machine Learning
Professional Practice Tests Help
You in the Preparation?
Yes, ML Engineer practice tests are beneficial in
offering you the actual exam-like conditions. With
the timed system, you become skilled in time
management and know exactly how much time you
should spend on each question.
Moreover, you learn about your flaws by analyzing
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individual score high in the actual exam.
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Machine Learning Professional practice questions.
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Machine Learning Professional
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