[MUSIC] And we have now seen how to
build a decision tree from data. It's pretty cool, simple,
really recursive algorithm, main choice to be made is what feature
to split on and when to stop splitting. In the next module we're going to talk
about ways to address over fitting in decision trees. But you should be ready now to understand
how to build a decision tree from data, really implement that algorithm, and be able to make predictions from
the decision trees that you learn. As well as to explore decision
boundaries of decision trees and how they relate to decision boundaries
of say logistic regression. And let me close by thanking my colleague Krishna who was instrumental in making
the slides that you saw in this module. I really appreciate all the effort
that Krishna put into this. [MUSIC]