2 Get Started with Oracle Machine Learning User Interface

This section discusses how to get started with Oracle Machine Learning User Interface, and use Apache Zeppelin-based machine learning notebooks along with the Notebooks EA (Early Adopter), where you can perform data exploration and data visualization, data preparation and machine learning.

• Get Started with Oracle Machine Learning User Interface
  Here is how you can get started with Oracle Machine Learning User Interface (UI).
• Access Oracle Machine Learning User Interface
  You can access Oracle Machine Learning User Interface from Autonomous Database.
• About Oracle Machine Learning Notebooks
  Oracle Machine Learning Notebooks is a collaborative web-based interface that supports notebook creation, scheduled run, and versioning. You can document work using Markdown and run SQL, R, and Python code for data exploration, visualization, and preparation, and machine learning model building, evaluation, and deployment. Oracle Machine Learning Notebooks also provide the Conda interpreter to create a custom conda environment that includes user-specified third-party Python and R libraries.
• Oracle Machine Learning User Interface Home Page
  The Oracle Machine Learning User Interface home page provides you quick links to important interfaces, help links, and the log of your high-level recent activities.

2.1 Get Started with Oracle Machine Learning User Interface

Here is how you can get started with Oracle Machine Learning User Interface (UI).

1. Request access to Oracle Machine Learning UI. Contact your Service Administrator to create your OML user credentials and provide access to your Oracle Machine Learning UI account.
2. Access the Oracle Machine Learning UI account by using your credentials. In case you forget your password, then request the Administrator to reset it.

   Note:

   Once you receive your new password, you must change it immediately. Refer to the Oracle Machine Learning password policy for more information.
3. Once you log in for the first time, a workspace and project will be created for you. You can start creating your notebook. You can also create your additional projects in the default workspace or create new workspace with corresponding projects.

   Note:

   If you are using Oracle Cloud Free Tier, you have to provision an Oracle Autonomous Database. For more information, see Provision Autonomous Database

2.2 Access Oracle Machine Learning User Interface

You can access Oracle Machine Learning User Interface from Autonomous Database.

To access Oracle Machine Learning User Interface (UI) from the Autonomous Database:

1. Select your Autonomous Database instance and on the Autonomous Database details page click Database Actions.
2. On the Database Actions page, go to the Development section and click Oracle Machine Learning. The Oracle Machine Learning sign in page opens.
3. On the Oracle Machine Learning sign in page, enter your username and password.
4. Click Sign In.

This opens the Oracle Machine Learning user application.

• About Oracle Machine Learning Password Policy
  All Oracle Machine Learning users must follow the password policy to create a strong and secure password.

2.2.1 About Oracle Machine Learning Password Policy

All Oracle Machine Learning users must follow the password policy to create a strong and secure password.

When changing or modifying your Oracle Machine Learning password, ensure that you follow these conditions:

• The password must be between 12 and 30 characters long. It must include at least one uppercase letter, one lowercase letter, and one numeric character.

• The password cannot contain the username.

• The password cannot be one of the last 4 passwords used for the same username.

• The password cannot contain the double quote (") character.

• The password must not be the same password that is set less than 24 hours ago.

2.3 About Oracle Machine Learning Notebooks

Oracle Machine Learning Notebooks is a collaborative web-based interface that supports notebook creation, scheduled run, and versioning. You can document work using Markdown and run SQL, R, and Python code for data exploration, visualization, and preparation, and machine learning model building, evaluation, and deployment. Oracle Machine Learning Notebooks also provide the Conda interpreter to create a custom conda environment that includes user-specified third-party Python and R libraries.

Key features of Oracle Machine Learning Notebooks:

• Allows collaboration among data scientists, business and data analysts, application and dashboard developers, Database Administrators, and IT professionals

• Leverages the scalability and performance of Oracle Autonomous Database Platform

• Supports scheduling notebooks as jobs for one-off and recurring running of notebooks

• Enables versioning of notebooks

• Supports interpreters for SQL, PL/SQL, Python, R, Markdown, and Conda

• Typical Actions when Using Oracle Machine Learning Notebooks
  To begin with Oracle Machine Learning Notebooks, refer to the tasks listed in the table as a guide.

2.3.1 Typical Actions when Using Oracle Machine Learning Notebooks

To begin with Oracle Machine Learning Notebooks, refer to the tasks listed in the table as a guide.

Tasks	More Information
Access Oracle Machine Learning User Interface	Access Oracle Machine Learning User Interface (UI)
Create workspaces	Create Projects and Workspaces
Create projects	Create Projects and Workspaces
Create notebooks	Create a Notebook
Run a Notebook using Python Interpreter	Use the Python Interpreter in a Notebook Paragraph
Run a Notebook using R Interpreter	Use the R Interpreter in a Notebook Paragraph
Use the Scratchpad	Use the Scratchpad
Create jobs to schedule notebooks	Create Jobs to Schedule Notebook

2.4 Oracle Machine Learning User Interface Home Page

The Oracle Machine Learning User Interface home page provides you quick links to important interfaces, help links, and the log of your high-level recent activities.

Figure 2-1 Oracle Machine Learning UI Home Page

On the home page, you can access:

• The How Do I help links to:

  • Get Started
  • Use AutoML
  • Deploy Models
  • Monitor Data
  • Create Notebooks
  • Create Jobs
  • Manage Permissions
  • Try It
• The Quick Actions links to:

  • AutoML
  • Models
  • Data Monitoring
  • Scratchpad
  • Notebooks
  • Notebook Jobs
  • Examples

• The log of your Recent Activities.

• The application navigation by clicking on the top left corner of the home page.

• The options to select and create new projects, access recent projects, manage workspace, and set workspace permissions by clicking on the top right corner of the home page.

• The Recent Notebooks on the right pane of the home page.