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Oracle Cloud Infrastructure Data Science 2022 Professional Sample Questions (Q12-Q17):

NEW QUESTION # 12
You have trained three different models on your data set using Oracle AutoML. You want to visualize the behavior of each of the models, including the baseline model, on the test set. Which class should be used from the Accelerated Data Science (ADS) SDK to visually compare the models?

• A. ADS Evaluator
• B. ADS Explainer
• C. EvaluationMetrics
• D. ADSTuner

Answer: C

NEW QUESTION # 13
What preparation steps are required to access an Oracle AI service SDK from a Data Science notebook session?

• A. Call the Accented Data Science (ADS) command to enable Al integration
• B. Import the REST API
• C. Create and upload the API signing key and config file
• D. Create and upload execute.py and runtime.yaml

Answer: C

NEW QUESTION # 14
You have an embarrassingly parallel or distributed batch job on a large amount of data running using Data Science Jobs What would be the best approach to run the workload?

• A. Create the job in Data Science Jobs and start a job run. When it is done, start a new job run until you achieve the number of runs required.
• B. Reconfigure the job run because Data science jobs does not support embarrassingly parallel.
• C. Create the job in Data Science Jobs and then start the number of simultaneous job runs required for your workload.
• D. Create a new job for every job run that you have to run in parallel, because the Date Science Jobs service can have only one job run per job.

Answer: C

NEW QUESTION # 15
You have a data set with fewer than 1000 observations, and you are using Oracle AutoML to build a classifier. While visualizing the results of each stage of the Oracle AutoML pipeline, you notice that no visualization has been generated for one of the stages. Which stage is not visualized?

• A. Hyperparameter tuning
• B. Adaptive sampling
• C. Algorithm selection
• D. Feature selection

Answer: B

NEW QUESTION # 16
As a data scientist, you are tasked with creating a model training job that is expected to take different hyperparameter values on every run. What is the most efficient way to set those pa-rameters with Oracle Data Science Jobs?

• A. Create a new job every time you need to run your code and pass the parameters as en-vironment variables.
• B. Create your code to expect different parameters either as environment variables or as command line arguments, which are set on every job run with different values.
• C. Create a new no by setting the required parameters in your code, and create a new job for mery code change.
• D. Create your code to expect different parameters as command line arguments, and create it new job every time you run the code.

Answer: B

NEW QUESTION # 17
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