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Oracle Cloud Infrastructure Data Science 2023 Professional Questions and Answers

Question 1

You are a data scientist designing an air traffic control model, and you choose to leverage Oracle

AutoML You understand that the Oracle AutoML pipeline consists of multiple stages and

automatically operates in a certain sequence. What is the correct sequence for the Oracle AutoML

pipeline?

Options:

A.

Algorithm selection, Feature selection, Adaptive sampling, Hyperparameter tuning

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B.

Adaptive sampling, Algorithm selection, Feature selection, Hyperparameter tuning

C.

Adaptive sampling, Feature selection, Algorithm selection, Hyperparameter tuning

D.

Algorithm selection, Adaptive sampling, Feature selection, Hyperparameter tuning

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Question 2

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

parameters with Oracle Data Science Jobs?

Options:

A.

Create a new job every time you need to run your code and pass the parameters as

environment variables.

B.

Create a new job by setting the required parameters in your code and create a new job for

every code change.

C.

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.

D.

Create your code to expect different parameters as command line arguments and create a

new job every time you run the code.

Question 3

When preparing your model artifact to save it to the Oracle Cloud Infrastructure (OCI) Data Science model catalog, you create a score.py file. What is the purpose of the score.py fie?

Options:

A.

Define the compute scaling strategy.

B.

Configure the deployment infrastructure.

C.

Define the inference server dependencies.

D.

Execute the inference logic code