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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.
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