Pass Your Oracle Cloud 1z0-1110-23 Exam on May 04, 2024 with 80 Questions
1z0-1110-23 Free Exam Study Guide! (Updated 80 Questions)
Oracle 1z0-1110-23 Exam Syllabus Topics:
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NEW QUESTION # 41
As you are working in your notebook session, you find that your notebook session does not have enough compute CPU and memory for your workload. How would you scale up your notebook session without losing your work?
- A. Down your files and data to your local machine, delete your notebook session, provision tebook session on a larger compute shape, and upload your files from your local the new notebook session.
- B. Ensure your files and environments are written to the block volume storage under the /home/datascience directory, deactivate the notebook session, and activate the notebook larger compute shape selected.
- C. Deactivate your notebook session, provision a new notebook session on larger compute shape, and re-create all your file changes.
- D. Create a temporary bucket in Object Storage, write all your files and data to Object Storage, delete tur ctebook session, provision a new notebook session on a larger compute shape, and capy your flies and data from your temporary bucket onto your new notebook session.
Answer: B
NEW QUESTION # 42
You train a model to predict housing prices for your city. Which two metrics from the Accelerated Data Science (ADS) ADSEvaluator class can you use to evaluate the regression model?
- A. Mean Absolute Error
- B. Weighted Recall
- C. Explained Variance Score
- D. Weighted Precision
- E. F-1 Score
Answer: B,C
NEW QUESTION # 43
As you are working in your notebook session, you find that your notebook session does not have enough compute CPU and memory for your workload.
How would you scale up your notebook session without losing your work?
- A. Ensure your files and environments are written to the block volume storage under the
/home/datascience directory, deactivate the notebook session, and activate the notebook session with a larger compute shape selected. - B. Deactivate your notebook session, provision a new notebook session on a larger compute shape and re-create all of your file changes.
- C. Download all your files and data to your local machine, delete your notebook session, provision a new notebook session on a larger compute shape, and upload your files from your local machine to the new notebook session.
- D. Create a temporary bucket on Object Storage, write all your files and data to Object Storage, delete your notebook session, provision a new notebook session on a larger compute shape, Want any exam dump in pdf email me at [email protected] (Little Paid) and copy your files and data from your temporary bucket onto your new notebook session.
Answer: A
NEW QUESTION # 44
You are creating an Oracle Cloud Infrastructure (OCI) Data Science job that will run on a recurring basis in a production environment. This job will pick up sensitive data from an Object Storage bucket, train a model, and save it to the model catalog.
How would you design the authentication mechanism for the job?
- A. Store your personal OCI config file and keys in the Vault and access the Vault through the job run resource principal.
- B. Package your personal OCI config file and keys in the job artifact
- C. Use the resource principal of the job run as the signer in the job code, ensuring there is a dynamic group for this job run with appropriate access to Object Storage and the model catalog.
- D. Create a pre-authenticated request (PAR) for the Object Storage bucket, and use that in the job code.
Answer: C
NEW QUESTION # 45
The feature type TechJob has the following registered validators:
Tech-Job.validator.register(name='is_tech_job', handler=is_tech_job_default_handler) Tech-Job.validator.register(name='is_tech_job', handler= is_tech_job_open_handler, condi-tion=('job_family',)) TechJob.validator.register(name='is_tech_job', handler= is_tech_job_closed_handler, condition=('job_family': 'IT')) When you run is_tech_job(job_family='Engineering'), what does the feature type validator system do?
- A. Execute the is_tech_job_closed_handler handler.
- B. Execute the is_tech_job_default_handler sales handler.
- C. Throw an error because the system cannot determine which handler to run.
- D. Execute the is_tech_job_open_handler handler.
Answer: C
NEW QUESTION # 46
You loaded data into Oracle Cloud Infrastructure (OCI) Data Science. To transform the data, you want to use the Accelerated Data Science (ADS) SDK. When you applied the get_recommendations () tool to the ADSDataset object, it showed you user-detected issues with all the recommended changes to apply to the dataset. Which option should you use to apply all the recommended transformations at once?
- A. get_transformed_dataset ()
- B. visualize_transforms ()
- C. auto_transform()
- D. fit_transform()
Answer: C
NEW QUESTION # 47
Which Oracle Accelerated Data Science (ADS) classes can be used for easy access to data sets from reference libraries and index websites such as scikit-learn?
- A. ADSTuner
- B. DatasetBrowser
- C. SecretKeeper
- D. DataLabeling
Answer: B
NEW QUESTION # 48
You want to use ADSTuner to tune the hyperparameters of a supported model you recently trained. You have just started your search and want to reduce the computational cost as well as access the quality of the model class that you are using.
What is the most appropriate search space strategy to choose?
- A. Perfunctory
- B. ADSTuner doesn't need a search space to tune the hyperparameters.
- C. Detailed
- D. Pass a dictionary that defines a search space
Answer: A
NEW QUESTION # 49
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?
- A. Define the inference server dependencies.
- B. Execute the inference logic code
- C. Define the compute scaling strategy.
- D. Configure the deployment infrastructure.
Answer: D
NEW QUESTION # 50
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?
- A. Update the deployment to use a larger virtual machine (mare CPUs/memory).
- B. Update the deployment to use fewer instances.
- C. Update the deployment to add more instances.
- D. Reduce the load balancer bandwidth limit so that fewer requests come in.
- E. Delete the deployment.
Answer: C
NEW QUESTION # 51
You are a data scientist leveraging the Oracle Cloud Infrastructure (OCI) Language AI service for various types of text analyses. Which TWO capabilities can you utilize with this tool?
- A. Topic classification
- B. Punctuation correction
- C. Sentiment analysis
- D. Sentence diagramming
- E. Table extraction
Answer: A,C
NEW QUESTION # 52
After you have created and opened a notebook session, you want to use the Accelerated Data Science (ADS) SDK to access your data and get started with an exploratory data analysis.
From which two places can you access or install the ADS SDK?
- A. Python Package Index (PyPI
- B. Oracle Big Data Service
- C. Oracle Autonomous Data Warehouse
- D. Oracle Machine Learning (OML)
- E. Conda environments in Oracle Cloud Infrastructure (OCI) Data Science
Answer: A,E
NEW QUESTION # 53
You have a complex Python code project that could benefit from using Data Science Jobs as it is a repeatable machine learning model training task. The project contains many subfolders and classes.
What is the best way to run this project as a Job?
- A. Rewrite your code so that it is a single executable Python or Bash/Shell script file.
- B. ZIP the entire code project folder and upload it as a Job artifact. Jobs automatically identifies the_main_ top level where the code is run.
- C. ZIP the entire code project folder and upload it as a Job artifact on job creation. Jobs identifies the main executable file automatically.
- D. ZIP the entire code project folder, upload it as a Job artifact on job creation, and set JOB_RUN_ENTRYPOINT to point to the main executable file.
Answer: D
NEW QUESTION # 54
As a data scientist, you create models for cancer prediction based on mammographic images.
The correct identification is very crucial in this case. After evaluating two models, you arrive at the following confusion matrix.
Model 1 has Test accuracy is 80% and recall is 70%.
* Model 2 has Test accuracy is 75% and recall is 85%.
Which model would you prefer and why?
- A. Model 1, because recall has lesser impact on predictions in this use case
- B. Model 1, because the test accuracy is high.
- C. Model 2, because recall is high.
- D. Model 2, because recall has more impact on predictions in this use se.
Answer: D
NEW QUESTION # 55
You are working as a data scientist for a healthcare company. They decide to analyze the data to find patterns in a large volume of electronic medical records. You are asked to build a PySpark solution to analyze these records in a JupyterLab notebook. What is the order of recommended steps to develop a PySpark application in Oracle Cloud Infrastructure (OCI) Data Science?
- A. Install a Spark conda environment. Configure core-site.xml. Launch a notebook session.
Create a Data Flow application with the Accelerated Data Science (ADS) SDK. Develop your PySpark application. - B. Develop your PySpark application. Create a Data Flow application with the Accelerated Data Science (ADS) SDK.
- C. Launch a notebook session. Configure core-site.xml. Install a PySpark conda environment.
- D. Configure core-site.xml. Install a PySpark conda environment. Create a Data Flow application with the Accelerated Data Science (ADS) SDK. Develop your PySpark application. Launch a notebook session.
- E. Launch a notebook session. Install a PySpark conda environment. Configure core-site.xml.
Develop your PySpark application. Create a Data Flow application with the Accelerated Data Science (ADS) SDK.
Answer: E
NEW QUESTION # 56
You have created a Data Science project in a compartment called Development and shared it with a group of collaborators. You now need to move the project to a different compartment called Production after completing the current development iteration.
Which statement is correct?
- A. You cannot move a project to a different compartment after it has been created.
- B. Moving a project to a different compartment requires deleting all its associated notebook sessions and models first.
- C. Moving a project to a different compartment also moves its associated notebook sessions and models to the new compartment.
- D. You can move a project to a different compartment without affecting its associated notebook sessions and models
Answer: C
NEW QUESTION # 57
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 ora-cle_automl and now you want an output with all the different trials performed by Oracle Au-toML. Which of the following command gives you the results of all the trials?
- A. Oracle.automl.print_trials()
- B. Oracle.automl.visualize_adaptive_sampling_trails()
- C. Oracle.automl.visualize_tuning_trails()
- D. Oracle.automl.visualize_algorith_selection_trails()
Answer: A
NEW QUESTION # 58
During a job run, you receive an error message that no space is left on your disk device. To solve the problem, you must increase the size of the job storage. What would be the most efficient way to do this with Data Science Jobs?
- A. On the job run, set the environment variable that helps increase the size-of the storage.
- B. Edit the job, change the size of the storage of your job, and start a new job run.
- C. Your code is using too much disk space. Refactor the code to identify the problem.
- D. Create a new job with increased storage size and then run the job.
Answer: B
NEW QUESTION # 59
As a data scientist, you are working on a global health data set that has data from more than 50 countries. You want to encode three features such as 'countries', 'race' and 'body organ' as categories.
Which option would you use to encode the categorical feature?
- A. DataFrameLabelEncoder ()
- B. auto_transform()
- C. OneHotEncoder ()
- D. show_in_notebook ()
Answer: A
NEW QUESTION # 60
You want to ensure that all stdout and stderr from your code are automatically collected and logged, without implementing additional logging in your code. How would you achieve this with Data Science Jobs?
- A. You can implement custom logging in your code by using the Data Science Jobs logging service.
- B. Create your own log group and use a third-party logging service to capture job run details for log collection and storing.
- C. Make sure that your code is using the standard logging library and then store all the logs to Object Storage at the end of the job.
- D. On job creation, enable logging and select a log group. Then, select either a log or the option to enable automatic log creation.
Answer: D
NEW QUESTION # 61
The Accelerated Data Science (ADS) model evaluation classes support different types of machine learning modeling techniques. Which three types of modeling techniques are supported by ADS Evaluators?
- A. Principal Component Analysis
- B. Binary Classification
- C. K-means Clustering
- D. Multiclass Classification
- E. Recurrent Neural Network
- F. Regression Analysis
Answer: B,D,F
NEW QUESTION # 62
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