Online Access Free 1z0-1110-22 Exam Questions

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 dat a. Which of the following THREE statements are correct with respect to installing additional Python libraries to process the data?

• A.You can install private or custom libraries from your own internal repositories
• B.OCI Data Science allows privileges in notebook sessions.
• C.You can only install libraries using yum and pip as a normal user
• D.You can install any open source package available in a publicly accessible Python Package Index (PyPI) repository
• E.You cannot install a library that's not preinstalled in the provided image

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 exploratory data analysis. From which TWO places can you access the ADS SDK?

• A.Oracle Machine Learning
• B.Oracle Autonomous Data Warehouse
• C.Conda environments in Oracle Cloud infrastructure (OCI) Data Science.
• D.Oracle Big Data Service
• E.Python Package Index (PyPi)

Using Oracle AutoML, you are tuning hyperparameters on a supported model class and have specified a time budget. AutoML terminates computation once the time budget is exhausted. What would you expect AutoML to return in case the time budget is exhausted before hy-perparameter tuning is completed?

• A.The current best-known hyperparameter configuration is returned.
• B.A hyperparameter configuration with a minimum learning rate is returned.
• C.The last generated hyperparameter configuration is returned.
• D.A random hyperparameter configuration is returned.

You are a data scientist designing an air traffic control model, and you choose to leverage Or-acle 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?

• A.Adaptive sampling, Algorithm selection, Feature selection, Hyperparameter tuning.
• B.Algorithm selection, Feature selection, Adaptive sampling, Hyperparameter tuning.
• C.Adaptive sampling, Feature selection, Algorithm selection, Hyperparameter tuning.
• D.Algorithm selection, Adaptive sampling. Feature selection, Hyperparameter tuning.

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.Deactivate your notebook session, provision a new notebook session on larger compute shape, and re-create all your file changes.
• B.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.
• C.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.
• 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 com-pute shape, and capy your flies and data from your temporary bucket onto your new notebook session.