"While there have been advances in artificial intelligence (AI) this year, it's poised to skyrocket in 2019.." So a dozen articles a week begin. But what does this mean to me?

I basically understand that "General AI" or computers that can comprehend a wide range of topics and interests, just like people do, is still a long way off

However, Machine Learning is here right now. Teaching a model with real-world data and then predicting events using statistics is viable.

I don't pretend to understand the ins and outs of the complex mathematics that underpin machine learning. However, is there something in it for an average guy with a bit of experience in managing systems and software development?

I decided to do a course to see!

The course I picked was the Google "Crash Course in Machine Learning"

I'd already tried a few things with Tensorflow and this course used Tensorflow as it's a basic framework

The course covers the high-level theories that are used to build models, gather data and refine the predictions. There are about 20 hours of videos and practical exercises using a Jupiter-notebook alike Machine Learning playpen

To me the best realisation was in one of the later sections, summarised in this diagram

The tiny blue section is the super clever stuff with lots of complex maths

The rest of the sections are, basically, tradition data handling practices. If you have experience with moving data about, cleaning it and other usual validation processes then most of the mysterious world of Machine Learning is something you already know!

So it's well worth doing this course to see how your existing skills and experience fit in with the up and coming Machine Learning scene