Oracle 1z0-1096-23 Dumps

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Create User: An administrator creates a new user account and user credentials for Oracle Machine Learning in the User Management interface. Note: You must have the administrator role to access the Oracle Machine Learning User Management interface. To create a user account: Select an Autonomous Da-ta Warehouse instance and on the details page click Service Console. On the Service Console click Administration. Click Manage OML Users to open the Oracle Machine Learning User Administration page. Click Create on the Oracle Machine Learning User Administration page. In the Username field, enter a username for the account. Using the username, the user will log in to an Oracle Ma-chine Learning instance. Enter a name in the First Name field. Enter a name in the Last Name field. In the Email Address field, enter the email ID of the user. Select the option Generate password and email account details to user. User will be required to reset the password on first sign in. to auto generate a temporary password and send an email with the account credentials to the user. If you select this option, you need not enter values in the Password and Confirm Password fields; the fields are grayed out. In the Password field, enter a password for the user, if you choose to create a password for the user.This option is disabled if you select the Generate password... option to auto generate a temporary password for the user. In the Confirm Password field, enter a password to confirm the value that you entered in the Password field.By doing so, you create the password for the user. The user can change the password when first logging in. Click Create. This creates a new database user and grants the required privileges to use Oracle Machine Learning.

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• The step that is not required to be performed by an administrator when adding a new user to Oracle Machine Learning Notebooks is providing the user with Autonomous Database client wallet for remote credentials.
• The client wallet is only needed for remote access to the database using tools such as SQL Developer or Python. For accessing Oracle Machine Learning Notebooks, the user only needs an OML username and password, which are created by the administrator in the Oracle Machine Learning User Management interface

• A false statement regarding Oracle Machine Learning (OML) is that OML offerings need a separate data visualization tool for creating visualization56.
• OML does not need a separate data visualization tool for creating visualization because it provides various options for visualizing data and models within its offerings. For example, OML Notebooks support interactive charts and graphs using Plotly and Matplotlib libraries for Python and R. OML SQL also supports native SQL functions for creating histograms, scatter plots, box plots, and more

• Classification algorithms are supervised learning methods that assign cases to target categories based on a set of input features12. For example, a classification algorithm can predict whether an email is spam or not based on its content and sender.
• Classification algorithms require known outcomes to guide the learning process, which means they need labeled data for training and evaluation12. For example, a classification algorithm can learn from a set of emails that are already labeled as spam or not by humans

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This is from Oracle Course : Using Oracle Machine Learning with Autonomous Database Regression is a supervised learning technique used when the output attribute is a continuous numerical value, for example, the price of a property based on the attributes of the property and its locality, the humidity of an area, and so on. Here is a list of all the algorithms offered by Oracle Machine Learning. Unsupervised learning does not involve direct control from the developer. In terms of defining an output attribute, the output attribute is a dependent attribute. And as there is no output attribute in unsupervised learning, there is no distinction between dependent and independent attributes.

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• View notebooks. An Administrator can view notebooks in their own workspace or in workspaces where they have collaboration rights. However, an Administrator cannot run or modify notebooks1.
• Reassign workspaces to users. An Administrator can reassign workspaces from one user to another user in the User Data page. This can be useful when a user leaves the organization or changes roles2.
• Create, edit and delete OML users. An Administrator can create new OML user accounts and passwords, edit existing OML user information, and delete OML users in the User Management interface.

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Unsupervised machine learning uses a more independent approach, in which a computer learns to identify complex processes and patterns without a human providing close, constant guidance. Un-supervised machine learning involves training based on data that does not have labels or a specific, defined output. To continue the childhood teaching analogy, unsupervised machine learning is akin to a child learning to identify fruit by observing colors and patterns, rather than memorizing the names with a teacher's help. The child would look for similarities between images and separate them into groups, assigning each group its own new label. Examples of unsupervised machine learning algorithms include k-means clustering, principal and independent component analysis, and association rules.

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• A false statement about OML Notebooks is that an existing database user cannot be added as an OML user using the User Management Interface2.
• An existing database user can be added as an OML user using the User Management Interface by entering the existing database username and password in the Create User dialog box. This will enable the existing database user to access OML Notebooks without creating a new schema2.

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• The three Oracle Machine Learning (OML) components that are available with Oracle Autonomous Database are OML Notebooks, OML4SQL, and OML Services2.
• OML Notebooks are web-based interfaces for data analysis, data discovery, data visualization, and collaboration based on Apache Zeppelin notebook technology. They support SQL, PL/SQL, Python, R, and markdown interpreters on Oracle Autonomous Database2.
• OML4SQL is a set of in-database machine learning algorithms and SQL functions that enable data exploration, data preparation, model building, evaluation, and deployment using SQL and PL/SQL on Oracle Autonomous Database2.
• OML Services are RESTful web services that enable users to build, deploy, and manage machine learning models using REST APIs on Oracle Autonomous Database. They support native in-database models and ONNX-format models for classification, regression, and clustering2

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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

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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.

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