Preface

We humans are since the beginning of the development of modern computers obsessed with creating computers that have super powers. Even before the birth of computers research has been done on artificial intelligence (AI). The question what artificial intelligence really is, is hard and fuel for philosophical discussions.

Currently (as of writing 2019) we see more and more products developed that claim to have super powers that come close to AI. A look under the surface shows that the real progress on AI is made by a tangible technique, called machine learning.

Machine learning today is able of solving challenging problems that impact everyone around the world. Problems that were impossible to solve for long or where too expensive or too complex to solve. Now solving these problems is possible using this new machine learning technology. Currently very complex problems and meaningful problems are solved using applications based on machine learning algorithms. Many firms involved are willing to tell and show you how easy it is! But you must be aware: machine learning is a buzzword in the industry! So the ML field is full of companies that use fads, all kind of vendor lock-in options and marketing buzz to take your money without delivering long running solutions.

This publication is aimed to give you solid information so you can start applying the new machine learning tools and frameworks too. However with no strings attached. So the focus for this publication is on openness. The core focus is outlining concepts and showing an open architecture that make machine learning possible for real business use cases. And of course this publication is focused on outlining open source solutions that make it possible to start your machine learning journey. So the aim of this book is to be a practical grounding in open machine learning and its business applications. This to help you transform your organization into an innovative, efficient, and sustainable company of the future using new open machine learning technology.

Machine learning is and should not be the exclusive domain commercial companies, data scientists, mathematics, computer scientists or hackers. Our belief is that every business and everyone should be able to take advantage of the machine learning techniques and applications available. This is possible within the field of machine learning as we will show in this publication.

Nowadays knowledge is more and more openly shared, thanks to open access, open publication licenses and open source software. So everyone can and should benefit from the possibilities that open machine learning frameworks and tools provide.

To create this publication a lot of papers, books and reports on machine learning have been examined. And doing crucial ‘hands-on’ to experiences and feel the power of machine learning algorithms turned out to be crucial for understanding and creating this publication.

In the journey on learning how to apply machine learning for real business cases many books turned out to be either too theoretical, or to much focused on programming algorithms only. As an IT architect I missed the overall machine learning picture from an typical architecture point of view. So business, information, application, infrastructure, security and privacy perspective. This books fills up that gap.

This publication is not an end, but is constructed as an continuous effort to provide usable open and non commercial information for applying machine learning technology.

This publication was only possible with the help of you! If you have a suggestion or corretion, please send an email to info [at] bm-support [dot] org. Ik will add you to the contributor list, unless you ask to be omitted.