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Oracle Updated 1z0-1110-23 Exam Questions and Answers by dhruv

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Oracle 1z0-1110-23 Exam Overview :

Exam Name: Oracle Cloud Infrastructure Data Science 2023 Professional
Exam Code: 1z0-1110-23 Dumps
Vendor: Oracle Certification: Oracle Cloud Infrastructure Certification
Questions: 80 Q&A's Shared By: dhruv
Question 20

You want to write a Python script to create a collection of different projects for your data science

team. Which Oracle Cloud Infrastructure (OCI) Data Science interface would you use?

Options:

A.

The OCI Software Development Kit (SDK)

B.

OCI Console

C.

Command line interface (CLI)

D.

Mobile App

Discussion
Question 21

You are a data scientist leveraging Oracle Cloud Infrastructure (OCI) Data Science to create a

model and need some additional Python libraries for processing genome sequencing data. Which of

the following THREE statements are correct with respect to installing additional Python libraries to

process the data?

Options:

A.

You can only install libraries using yum and pip as a normal user.

B.

You can install private or custom libraries from your own internal repositories.

C.

OCI Data Science allows root privileges in notebook sessions.

D.

You can install any open source package available on a publicly accessible Python Package

Index (PyPI) repository.

E.

You cannot install a library that's not preinstalled in the provided image

Discussion
Question 22

. You realize that your model deployment is about to reach its utilization limit. What would you do

to avoid the issue before requests start to fail?

Options:

A.

Update the deployment to add more instances.

B.

Delete the deployment.

C.

Update the deployment to use fewer instances.

D.

Update the deployment to use a larger virtual machine (more CPUs/memory).

E.

Reduce the load balancer bandwidth limit so that fewer requests come in.

Discussion
River
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Aleksander Nov 26, 2025
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Question 23

While reviewing your data, you discover that your data set has a class imbalance. You are aware

that the Accelerated Data Science (ADS) SDK provides multiple built-in automatic transformation

tools for data set transformation. Which would be the right tool to correct any imbalance between

the classes?

Options:

A.

visualize_transforms ()

B.

auto_transform()

C.

sample ()

D.

suggest_recommendations()

Discussion
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