1z0-1096-23 Practice Exam Questions with Answers Oracle Machine Learning using Autonomous Database 2023 Associate Certification

Explanation

Oracle Machine Learning Notebooks is an Apache Zeppelin-based collaborative web-based inter-face that provides a development environment to create machine learning notebooks where you can perform data exploration and visualizations, data preparation and machine learning. https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/get-started-oracle-machine-learning.html

• The three types of permissions that can be granted to a user to collaborate and access a workspace in Oracle Machine Learning Notebooks are Viewer, Manager, and Developer1.
• Viewer is a user role that allows users to view notebooks but not run or modify them1.
• Manager is a user role that allows users to perform all the tasks of a Developer as well as manage other users’ workspaces and permissions1.
• Developer is a user role that allows users to create and run notebooks, run SQL statements, create SQL scripts, run Python scripts, create jobs to schedule and run notebooks, use example template notebooks, create and run AutoML experiments, and deploy models1.

• To share a notebook with a colleague to run on a different Autonomous Database instance, you should export the notebook in .json format and have your colleague import this notebook4.
• Exporting a notebook in .json format preserves the content and format of the notebook, including the code cells, text cells, images, charts, and graphs. You can export a notebook from the Notebook menu or from the Notebooks page4.
• Importing a notebook in .json format allows you to upload an existing notebook file to your workspace and run it on your Autonomous Database instance. You can import a notebook from the Notebooks page or from the Create Notebook dialog box4.

When managing machine learning models using the OML AutoML UI, three actions that can be performed on Oracle Machine Learning (OML) models from within OML AutoML UI are:

• Create a notebook with auto-generated OML4Py code from an OML in-database model to allow for further model tweaking and batch scoring. This feature enables users to export the selected model as a notebook that contains the OML4Py code to reproduce the model building process and perform additional tasks such as model evaluation, scoring, or deployment1.
• Deploy an OML in-database model to a REST endpoint. This feature enables users to deploy the selected model as a RESTful web service that can be accessed by external applications or tools for real-time scoring or predictions2.
• Review the model statistics associated with the experiment of an OML in-database model. This feature enables users to view the details of the model such as the algorithm name, hyperparameters, performance metrics, feature importance, and confusion matrix3.

Explanation

https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/grant-workspace-permissions.html https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/workspace-permissions.html

Explanation

https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/notebooks-templates.html

• Running this command will return the median value of customer credit limit grouped by marital status2.
• The MEDIAN function is an aggregate function that returns the middle value of a numeric column for each group or partition. If the number of values is even, it returns the average of the two middle values2.
• The GROUP BY clause is used to divide the rows of a table into groups that have the same values in the specified columns. The aggregate functions are applied to each group separately and the result is returned for each group3.

Explanation

https://www.oracle.com/a/tech/docs/otn-batch1/oml-automl-ui-tech-brief.pdf https://docs.oracle.com/en/database/oracle/machine-learning/oml-automl-ui/amlui/create-experiment.html

Explanation

About Workspace Permission Types: Oracle Machine Learning allows three types of permissions. Depending on the permission type, you can allow the user to view or perform different tasks in your workspace, projects, and notebooks. The three types of permissions are listed in the following table along with the actions that are allowed. Permission Types || Actions based on permission > Manager: • Project: Create, update, delete. • Workspace: View only. • Notebooks: Create, update, run, delete, and schedule jobs. > Developer: • Project: View only. • Workspace: View only. • Notebooks: Cre-ate, update, run, and delete notebooks that a developer creates only. • Jobs: View and run jobs of shared notebooks only. A developer cannot create jobs for notebooks that are shared. > Viewer: • Project: View only. • Workspace: View only. • Notebooks: View only. • Jobs: View jobs and job runs of shared notebooks only.

Explanation

%sql - Allows you to run SQL statements. Use the Scratchpad The Scratchpad provides you convenient one-click access to a notebook for running SQL statements, PL/SQL scripts, and Python scripts that can be renamed. The Scratchpad is available on the Oracle Machine Learning Notebooks home page. Note: The Scratchpad is a regular notebook that is prepopulated with three paragraphs - %sql, %script, and %python. After you run your scripts, the Scratchpad is automatically saved as a notebook by the default name Scratchpad in the Notebooks page. You can access it later in the Notebooks page. You can run all the paragraphs together or one paragraph at a time. To open and use the scratchpad, click Scratchpad on the Oracle Machine Learning Notebooks home page under Quick Actions. The Scratchpad opens. The Scratchpad has three paragraphs each with the following directives:%sql - Allows you to run SQL statements.%script - Allows you to run PL/SQL scripts.%python - Allows you to run Python scripts.

Explanation

https://learn.oracle.com/ols/course/using-oracle-machine-learning-with-autonomous-database/35644/98086/149312

Explanation

https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/use-library-collaborate-users.html#GUID-F468F691-2B8B-4427-B517-5F149AA57239 Use Templates to Collaborate with Users In the Oracle Machine Learning Templates UI, you can collaborate with other users by sharing your work, publishing your work as reports, and by creating notebooks from tem-plates. You can store your notebooks as templates, share notebooks, and provide sample templates to other users. Note: You can also collaborate with other Oracle Machine Learning Notebook users by providing access to your workspace. The authenticated user can then access the projects in your workspace, and access your notebooks. The access level depends on the permission type granted - Manager, Developer, or Viewer. For more information about collaboration among users, see unre-solvable-reference.html#GUID-7079D42F-9308-4BEF-B2F2-E74E49A22A87 Use the Personal Templates Personal Templates lists the notebook templates that you have created. Use the Shared Templates In the Shared Templates, you can share notebook templates with all authenticated users the notebook templates you create from existing notebooks available in Templates. Use the Example Templates The Example Templates page lists the pre-populated Oracle Machine Learning notebook templates. You can view and use these templates to create your notebooks.

Explanation

https://docs.oracle.com/en/cloud/paas/autonomous-database/adbsa/create-notebooks-oml.html#GUID-0F489564-A628-478E-9898-1F94B0441026

Explanation

Oracle Machine Learning Notebooks Increase data scientist and developer productivity and reduce their learning curve with familiar open source-based Apache Zeppelin notebook technology. Note-books support SQL, PL/SQL, Python, and markdown interpreters for Oracle Autonomous Database so users can work with their language of choice when developing models. View interactive product tour Oracle Machine Learning Notebooks with Autonomous Data Warehouse documentation Oracle Machine Learning Notebooks with Autonomous Transaction Processing documentation Oracle Ma-chine Learning Notebooks with Autonomous JSON Database documentation

Explanation

https://docs.oracle.com/en/database/oracle/machine-learning/oml-notebooks/omlug/get-started-oracle-machine-learning.html#GUID-13452045-6AF6-402B-83CC-C9AFBCEC30CA Typical Workflow For Using Notebooks To begin with Oracle Machine Learning Notebooks, refer to the tasks listed in the table as a guide. TasksMore InformationAccess Oracle Machine Learning Note-booksAccess Oracle Machine LearningCreate workspacesCreate Projects and WorkspacesCreate projectsCreate Projects and WorkspacesCreate notebooksCreate a NotebookRun a Notebook with Python InterpreterRun a Notebook with Python InterpreterUse the ScratchpadUse the Scratchpad-Create jobs to schedule notebooksCreate Jobs to Schedule Notebook

Explanation

https://docs.oracle.com/en/database/oracle/machine-learning/oml-automl-ui/amlui/create-experiment.html