If someone wants to investigate artificial intelligence and machine learning for their own organization, what are some practical steps they can take?
The key to any data science project is data. There’s an 80/20 rule for everything. And in this case, it’s 80% data understanding, data manipulation, and data preparation, and 20% modeling and validation on the backside.
I’d say that the key to getting started is having some very clever and curious people around. We have a great team of data scientists, data analysts, and data engineers who work really closely with our program management department to build models that are sustainable and prioritize our values for our customers.
Investigate what data you have available to use or what data you can make available. We purchase external data from some of our partner vendors that help us supplement our internal house data. We’re also constantly attending industry events and staying current with new modeling techniques that may be available.
So it’s really staying curious, staying current, having the right data, and just getting started. You have to do some trial and error and learn as you figure things out. Don’t be afraid to give it a try.
