1z0-1110-22 無料問題集「Oracle Cloud Infrastructure Data Science 2022 Professional」

（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）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.

（C）Deactivate your notebook session, provision a new notebook session on larger compute shape, and re-create all your file changes.

（D）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.

（A）Oracle Autonomous Data Warehouse

（B）Conda environments in Oracle Cloud infrastructure (OCI) Data Science.

（C）Python Package Index (PyPi)

（D）Oracle Big Data Service

（E）Oracle Machine Learning

（A）The file that was defined for them on the Virtual stachine (VM).

（B）The OCI console.

（C）The predict log in the Oracle Cloud Infrastructure (OCI) Logging service as defined in the deployment.

（D）The OCI Cloud Shell, which can be accessed from the console.

（A）Feature Dependence Explanations.

（B）Accumulated Local Effects.

（C）Feature Permutation Importance Explanations.

（D）Local Interpretable Model-Agnostic Explanations.

（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) SOK. Develop your PySpark application

（B）Develop your PySpark application. Create a Data Flow application with the Ac-celerated Data science (ADS) SDK.

（C）Launch a notebook session. Install a PySpark conda environment. Configure coresite. xml.

（D）Develop your PySpark application Create a Data Flow application with the Ac-celerated Data Science (ADS) SOK

（E）Configure core-site.xml. Install a PySPark conda environment. Create a Data Flow application with the Accelerated Data Science (ADS) SDK Develop your PySpark ap-plication. Launch a notebook session.

（F）Launch a notebook session. Configure core-site.xml. Install a PySPark conda environ-ment.

（A）Create your code to expect different parameters as command line arguments, and create it new job every time you run the code.

（B）Create a new no by setting the required parameters in your code, and create a new job for mery code change.

（C）Create a new job every time you need to run your code and pass the parameters as en-vironment variables.

（D）Create your code to expect different parameters either as environment variables or as command line arguments, which are set on every job run with different values.