Free Access Oracle.1z0-1110-25.v2025-11-29.q58 Practice Test (Page 6)

Question 21

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

A.Create a job in Data Science Jobs and then start the number of simultaneous job runs required for your workload

B.Create a new job for every job run that you have to run in parallel, because the Data Science Job service can have only one job per job

C.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

D.Reconfigure the job run because Data Science Jobs does not support embarrassingly parallel

Question 22

You have built a machine model to predict whether a bank customer is going to default on a loan. You want to use Local Interpretable Model-Agnostic Explanations (LIME) to understand a specific prediction. What is the key idea behind LIME?

A.Global behaviour of a machine learning model may be complex, while the local behaviour may be approximated with a simpler surrogate model

B.Model-agnostic techniques are more interpretable than techniques that are dependent on the types of models

C.Global and local behaviours of machine learning models are similar

D.Local explanation techniques are model-agnostic, while global explanation techniques are not

Question 23

Which statement accurately describes an aspect of machine learning models?

A.Model performance degrades over time due to changes in data.

B.Static predictions become increasingly accurate over time.

C.Data models are more static and generally require fewer updates than software code.

D.A high-quality model will not need to be retrained as new information is received.

Question 24

You are using Oracle Cloud Infrastructure (OCI) Anomaly Detection to train a model to detect anomalies in pump sensor data. How does the required False Alarm Probability setting affect an anomaly detection model?

A.It is used to disable the reporting of false alarms

B.It changes the sensitivity of the model to detecting anomalies

C.It determines how many false alarms occur before an error message is generated

D.It adds a score to each signal indicating the probability that it's a false alarm

Question 25

Why is data sampling useful for data scientists?

A.It lets them analyze datasets in small batches to reduce their use of system resources.

B.It reduces the amount of data storage space that's required for data science applications.

C.It enables them to use a representative subset of data to build accurate analytical models more quickly.

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