Oracle Autonomous Data Warehouse Cloud Service (ADW), Part 3: Getting Started with Oracle Machine Learning
This is the third post in a series, where I explain the summarized steps that show how to use the Oracle Autonomous databases.
This post explains how to use Oracle Machine Learning with the Oracle Autonomous Data Warehouse.
Oracle Machine Learning
Oracle Machine Learning is a collaborative web-based interface (based on Apache Zeppelin) that provides a development environment to create data science notebooks, SQL scripts, and other data analysis artifacts. With it, you can perform data analytics, data discovery, and data visualizations as well as reuse native, out-of-the-box machine learning algorithms.
The current version allows you to use SQL and PL/SQL, Python, and R, so it’s a good tool for data science, data analysis, and machine learning. Better, it’s co-located with Autonomous Data Warehouse databases.
The architectural diagram below shows how Oracle Machine Learning is comprised by ADW as an integral part of its components set.
So below are the summarized steps required to get access to Oracle Machine Learning Console.
Request Access to Oracle Machine Learning
First, you have to contact your Service Administrator in order to get access to your Oracle Machine Learning account.
The Administrator provides the required access permissions. In case you’re the Administrator for your environment yourself, please follow the steps below.
First, access the main screen of ADW from the Oracle Cloud Dashboard, then click the Autonomous Data Warehouse option:
Then on the screen below, click the Open Service Console button:
You will be taken to ADW’s main page. Click the link with your database name:
Now, click the Service Console button as shown below:
You will see the ADW’s Overview screen as shown below:
Select the Administration menu option, you will see the Administration screen:
Now, click Manage Oracle ML Users:
There you can define a new User Name, so just click the Create button:
Provide the required user information as per the example below:
After that, the target user will be notified and the new user will be listed as below:
Access the Oracle Machine Learning console
Then as soon as the new user is created and the permissions are granted, the new user will receive an email message with the related User Name, along with a temporary password and the link to Oracle Machine Learning Console.
The screenshots below show the email message about the account creation:
Click the Access Oracle ML SQL notebook button, change the password and you will see the Oracle Machine Learning Console and its landing page below:
That’s it! The next blog post will explain how to use the Oracle Machine Learning options, how to run scripts, work with Jupyter notebooks, and other features. Stay tuned!
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