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And we have now seen how to
build a decision tree from data.

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It's pretty cool, simple,
really recursive algorithm,

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main choice to be made is what feature
to split on and when to stop splitting.

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In the next module we're going to talk
about ways to address over fitting

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in decision trees.

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But you should be ready now to understand
how to build a decision tree from data,

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really implement that algorithm, and

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be able to make predictions from
the decision trees that you learn.

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As well as to explore decision
boundaries of decision trees and

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how they relate to decision boundaries
of say logistic regression.

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And let me close by thanking my colleague

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Krishna who was instrumental in making
the slides that you saw in this module.

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I really appreciate all the effort
that Krishna put into this.

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