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Pie & AI Suisse - On a business mission: From model to actionable interface

Now the correct day, May 13th!!!

Data Science projects often start with a question or a problem that arises out of a business department. Then it is time to collect, prepare, explore and understand the data. And finally, train a model and tune it to perfection. But what is next? How can the model be made accessible to external users to serve a business purpose? How do I explain the model output to somebody who has little to no understanding of machine learning? Although there is no single “right” way to answer all this, there is a bunch of opportunities to learn from in the real world.

So let’s shift our thinking away from where our data science projects start to where they end up: in an interface for users. This shift is important as the business value will once unfold if a user interacts smoothly with your model hopefully creating an extraordinary experience.
Time to set some basic requirements for such an interface to be successful: “Model output needs to be actionable and interpretable. Also, the output should be delivered in the business context by avoiding media breaks.” This leads us naturally to the goal of supporting business decisions. Okay so now that we have a great point to start from let’s take a look at what needs to happen to enable this.

In this session we will think about: Who needs to be involved? How to communicate ML results to users? What does an integration into legacy systems look like? And much more… - Together we will take a look at what is needed to successfully support decisions.

David Weik works as a Solutions Architect at SAS. He studied Business Informatics at the DHBW in Mannheim, Germany. Through his regular participation in hackathons, David discovered his passion for data and creating integrated customer-centric solutions. In his spare time, he enjoys hiking and movies.

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