Applications and Game Theory
Let's move into some of the major uses of machine learning in business.
The actual applications of machine learning in enterprise are too numerous to list – but it's easy to get a kind of background on how and why these projects are important.
One place to start is with the idea of game theory – the idea that you can create theoretical rational actors and run big data through a neural network or machine learning algorithm to see how outcomes among those actors will play out.
One of the easiest examples to think about is a busy fast food restaurant with a drive-through window. Every customer is a rational actor with his or her own desires and preferences. Each one is going to approach the physical restaurant location in his or her own way.
Using game theory, engineers can toss observed data about customers into a machine learning program and come up with results. Maybe they'll learn more about how to set up the drive-through. Maybe they'll figure out how to handle peak time demand. They may even get better insights about how people read the menu.
In the past, all of this was done with procedural logic tools. Now you can get deep inside of the human mind with game theory processes attached to innovative machine learning models.