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Author's profile photo Fred Verheul

What to expect from session ANP126 (Machine Learning) at SAPTechEd Barcelona, and what not…

Hi,

I just wanted to give everyone a quick idea of what my Community Session ANP126, “Machine Learning, Hype or Hit” is all about. In case you’re attending SAPTechEd Barcelona and considering attending the session, this should give you a better idea of what to expect and also what not to expect!

Machine Learning is very hot right now, but it’s a huge field, and even within 1 hour it’s hard to do it justice. Over the past couple of months, as I was working on the slides and deciding what I wanted to tell, I’ve had to make some tough choices about what to include and what to leave out.

So, let’s start with the things that didn’t make it into the presentation (right from the corresponding slide):

  • Deep Learning and Neural Networks
  • Specifics of ML algorithms
  • Tools / Libraries / Code
  • SAP Products, like HANA, Predictive Analytics, Vora, HCP predictive services, …

So, if we’re not going to discuss all these things, what’s left??

More than enough:

  • I’ll discuss some examples (including some cases of machine learning gone wrong and concerns around machine learning).
  • I’ll also try to make clear that machine learning is a toolset, used in a broader context. It’s certainly not a goal in and of itself!
  • Of course we’ll have a look at the different categories of machine learning tasks (supervised vs unsupervised, regression, classification, etc). There’s a lot of jargon being used in machine learning circles, and I’ll try to demystify some of it.
  • Then we’ll look more closely at the different categories of machine learning algorithms along three dimensions: representation, evaluation and optimization (I’ve borrowed this from Pedro Domingos).
  • A few general topics like how to handle your training data, risk of overfitting and distance metrics will be covered as well.
  • We’ll also shortly look at what skills and knowledge you need if you want to dive deeper into machine learning. However, if you’re interested in concrete resources, I’ll have to refer you to my networking session NET39386, later on Thursday (4PM).
  • I’ll finish the session with a recap of the key take-aways.

If this all sounds pretty high-level and qualitative instead of developer-like, you’re right. It came as a surprise to me as well, but I still think it’s the right order: before diving in and implementing this stuff, it’s good to have a basic understanding of what you’re doing, and it’s my sincere hope that this session will contribute to that understanding.

If you’ve made it so far, and are still interested, I hope to see you next week, Thursday Nov 10th at 14.15 at SAPTechEd Barcelona!

P.S. Couldn’t resist: I’m also not going to talk about the differences between all the terms below (thanks Timo Elliott)

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