Most Recent Oracle 1Z0-1096-23 Exam Dumps

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.

https://www.doag.org/formes/pubfiles/13151859/OE-DAC-Oracle-Machine-Learning-Overview-Whats-New-Customers-Apps_MLconcepts_Berger.pdf

Grant Workspace Permissions You can collaborate with other users in Oracle Machine Learning by granting permissions to access your workspace. Your workspace contains your projects and note-books. By granting different types of permissions such as Manager, Developer, and Viewer, you can allow another user to view your workspace and perform different tasks in your projects and note-books such as edit, create, update, delete, run, view notebooks and so on. For more information about the permission types, see About Workspace Permission Types. Caution: If you grant the per-mission type Manager or Developer, then the user can also drop tables, create tables, and run any scripts at any time on your account. The user with Viewer permission type can only view your note-books, and is not authorized to run or make any changes to your notebooks

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.

To segment your customer data for marketing research purposes and identify homogeneous groups to build supervised models, you should use clustering12.

Clustering is a type of unsupervised machine learning that groups data points based on their similarities in terms of features or attributes.Clustering can help discover the underlying structure of the data and reveal the natural segments or categories within it12.

Clustering can be useful for marketing research because it can help identify different types of customers based on their demographics, preferences, behaviors, or needs.Clustering can also help create customer profiles or personas that can be used to target specific segments with tailored marketing campaigns or offers12.

Clustering can also be used as a preliminary step for building supervised models, such as classification or regression.By using the cluster labels as an additional feature or a target variable, supervised models can learn from the cluster information and improve their accuracy or performance12.