Oracle Autonomous Data Warehouse Cloud Service (ADW), Part 3: Getting Started with Oracle Machine Learning

Oracle Machine Learning with ADW

by Juarez Junior

Introduction

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.

Autonomous Data Warehouse Architecture

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:

ADW access link

Then on the screen below, click the Open Service Console button:

Open Service Console

You will be taken to ADW’s main page. Click the link with your database name:

ADW DB link

Now, click the Service Console button as shown below:

ADW Service Console

You will see the ADW’s Overview screen as shown below:

ADW — Overview menu option

Select the Administration menu option, you will see the Administration screen:

ADW Administration menu option

Now, click Manage Oracle ML Users:

Manage Oracle ML Users

There you can define a new User Name, so just click the Create button:

Create ML user

Provide the required user information as per the example below:

ML user information

After that, the target user will be notified and the new user will be listed as below:

New ML username created

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:

Oracle Machine Learning — email notification

Oracle Machine Learning — account and access details

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:

Oracle Machine Learning page

Oracle Machine Learning — hamburger menu options

Wrapping up

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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