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Machine Learning in a Box (Part 4): Get Your Environment Up and Running

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Machine Learning in a Box (Part 4): Get Your Environment Up and Running

In the continuation of the the MLiaB series, we'll show you how to get your environment prepared and what you'll need to do it.

· AI Zone ·
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In case you are catching the train late, here is the link to the introduction blog of the Machine Learning in a Box series which allow you to get the series from the start. At the end of this introduction blog you will find the links for each elements of the series.

Before We Get Started, a Quick Recap from Last Week

Last week, we looked at the algorithm learning styles. I know that for many of you this is a lot of theory and I can already feel the impatience of some of you guys to start writing some.

So I will promise something from now on: there will be less theory and more hands on application!

There are 2 things that I learned by working with developers:

  • They all have their own set of tools and ways to use and customize them.
  • They will try to convince you that their choice is the best.

So I won't try to convince you to use A or B as a tool, except for one thing: SAP HANA, Express Edition!

SAP HANA, Express Edition will be at the core of this blog series (at least for now, but we will start looking at other technologies later too).

Hardware Specifications

(Sounds like a "PC Magazine from 90's" kind of section, doesn't it?)

So here is my Machine Learning Box:


Not the big one which is my SAP machine, but the small one: the Intel NUC!

This is little box (the 10 by 10 by 2.5 cm box) contains:

  • a i5-5250U Processor (2 cores)
  • 16 GB of DDR3 RAM
  • a 60 GB SSD drive
  • SUSE Linux Enterprise for SAP Applications

The big one is really big, it's a Lenovo P51 which contains:

  • a i7-7820HQ Processor (2 cores)
  • 64 GB of DDR3 RAM
  • a 500 GB + 1TB SSD drives
  • Windows 10 Pro

I use the big one to spin multiple virtual machines to play with large data set or long running processes.

But don't get scared, I won't expect you to have something like the big one; I will always keep in mind some minimum & maximum requirements.

So, the Intel NUC will be my "go to" choice.

If really don't have that kind of hardware, you will still be able to leverage some the cloud options.

What is SAP HANA, Express Edition?

What you will need is a SAP HANA, Express Edition Server only instance. As simple as that for the moment!

If you have a Server + Apps, that's fine but we won't use the application service for now.

The content I'll produce will be based on version 2.0 SPS02.

Many of you may already have their SAP HANA, Express Edition running either locally, as virtual machine, in the cloud or as a container, and that's great and let's see if you can use this one.

For those who don't have an instance running, I invite you to visit the SAP HANA, Express Edition product page on the SAP Developer Center. There, you will get all the informations to help you decide where you can run it and get your instance.

What's Next?

Once you have your instance running, you can run the following tutorial: Prepare your SAP HANA, Express Edition instance for Machine Learning.

You will get to choose what SQL query tool you will plan to work with. I have created content that addresses more or less every connectivity options (feel free to prove me wrong).

I have a personal preference for the SAP HANA Tools for Eclipse as I also use Eclipse for my Java development projects.

If you plan on using Eclipse, make sure you use either Neon or Oxygen, especially if you want to use the Docker image.

Anything else?

Off course, you will need a text editor, and maybe Excel. But that will do it for the moment.

Later, we might start playing with SAP Predictive Analytics or the R studio, but let's keep it simple.


Now, you should have your HXE tenant ready to run algorithms. Next week, where we will start uploading some dataset.

UPDATE: Here are the links to all the Machine Learning in a Box weekly blogs:

ai ,sap hana ,development tools ,environment ,sql query tool

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