Month: October 2018

RandomForests in R, Python and SQL

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I recently wrote a two part article explaining how Random Forests work and how to use them in R, Python and SQL.

These were posted on ToadWorld webpages. Check them out.

Part 1 of article


Part 2 of article


Creating and Managing OML users on Oracle ADWS

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(Check out my recent blog post on getting the ADWS up and running. You will need to have following those before you can perform the following steps.

In this post I’ll look at how to setup and manage users specifically for the Oracle Machine Learning (OML) tool. This tool is only available on ADWS and is a zeppelin based notebook for analytics, data science and machine learning.

1. Open the service console for ADWS and click on Administration
Administration can be found on the small menu list on the left hand side of the screen.

2. Click on Manage Oracle ML Users
As we are only interested in OML and Users for OML, just click on the section titled ‘Oracle ML Users’

3. Sign-in as Admin user
This user was created in my previous blog post. Hopefully you can remember the password.

4. Create a New User
The only user currently enabled for OML is the Admin user.
To create a new OML user click on the Create button


5. Enter OML User details
Enter the details of the OML user. Enter an email address and the person will receive an email with their login details. You have the choice of having a system generated password or uncheck the tick box and add in a password.
Click the Create button.
And hopefully the user will receive the email. The email may take a little bit of time to arrange in the users email box!

6. Log into Oracle Machine Learning

You have 2 options. The first is to follow the link in the email or click on the Home button on the top right hand side of the screen.

You will then be logged into Oracle Machine Learning. Look out for my blog posts on using this product and how to run the demos.


Slides from my OOW Presentation

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Here are the slides from my presentation (with Neil Chandler) at Oracle Open World and Oracle Code One.

1 – Code1-Nnets_REST-joint-ver2


Oracle 18c XE – Comes with in-database and R machine learning

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As of today 20th October, Oracle has finally released Oracle 18c XE aka Express Edition

A very important word associated with Oracle 18c XE is the word ‘FREE’

Yes it is FREE

This FREE product is backed full of features. Think of all the features that come with the Enterprise Edition of the Database. It comes with most of those features, including some of the extra add on features.

I said it comes with most features. There are a few features that don’t come with XE, so go check out the full list here.


There are a few restrictions:

  • Up to 12 GB of user data
  • Up to 2 GB of database RAM
  • Up to 2 CPU threads
  • Up to 3 Pluggable Databases

I know of so many companies and applications that easily meet the above restrictions.

For the Data Scientists and Machine Learning people, the Advanced Analytics option is now available with Oracle 18c XE. That means you can use the in-memory features for super fast analytics, use the in-database machine learning algorithms, and also use the embedded R feature called Oracle R Enterprise.

Yes you are limited to 12G of user data. That might be OK for most people but for those whose data is BIG then this isn’t an option for you.

There is a phrase, “Your data isn’t as big as you think”, so maybe your data might fit within the 12G.

Either way this can be a great tool to allow you to try out machine learning for Free in a test lab environment.

Go download load it and give it a try.


Creating an Autonomous Data Warehouse Cloud Service

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The following outlines the steps to create a Autonomous Data Warehouse Cloud Service.

Log into your Oracle Cloud account and then follow these steps.

1. Select Autonomous Data Warehouse Cloud service from the side menu


2. Select Create Autonomous Data Warehouse button


3. Enter the Compartment details (Display Name, Database Name, CPU Core Count & Storage)


4. Enter a Password for Administrator, and then click ‘Create Autonomous Data Warehouse’


5. Wait until the ADWC is provisioned

Going from this


to this


And you should receive and email that looks like this


6. Click on the name of the ADWS you created


7. Click on the Service Console button


8. Then click on Administration and then Download a Connection Wallet

Specify the password


You an now use this to connect to the ADWS using SQL Developer

All done.


R vs Python vs SQL for Machine Learning (Infographic)

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Next week I’ll be giving several presentation on machine learning at Oracle Open World and Oracle Code One. In one of these presentation an evaluation of using R vs Python vs SQL will be given and discussed.

Check out the infographic containing the comparisons.

Info Graphic