Oracle exactexam 1z0-1110-25 Questions Bank by Arjan q95 vce pdf

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Exam Name:	Oracle Cloud Infrastructure 2025 Data Science Professional
Exam Code:	1z0-1110-25 Dumps
Vendor:	Oracle	Certification:	Oracle Cloud Infrastructure
Questions:	158 Q&A's	Shared By:	arjan

Question 12

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

Options:

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

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

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

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

Discussion

Question 13

You are a data scientist working for a manufacturing company. You have developed a forecasting model to predict the sales demand in the upcoming months. You created a model artifact that contained custom logic requiring third-party libraries. When you deployed the model, it failed to run because you did not include all the third-party dependencies in the model artifact. What file should be modified to include the missing libraries?

Options:

model_artifact_validate.py

score.py

runtime.yaml

requirements.txt

Discussion

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Question 14

The Oracle AutoML pipeline automates hyperparameter tuning by training the model with different parameters in parallel. You have created an instance of Oracle AutoML as oracle_automl and now you want an output with all the different trials performed by Oracle AutoML. Which of the following commands gives you the results of all trials?

Options:

oracle_automl.print_trials()

oracle_automl.visualize_tuning_trials()

oracle_automl.visualize_adaptive_sampling_trials()

oracle_automl.visualize_algorithm_selection_trials()