01 · Understand the idea
In simple words
A decision tree makes a prediction through a series of questions. A simple plant-care tree might ask whether soil is dry, then whether the plant was watered recently. Small trees can be easy to follow. Very deep trees can learn tiny exceptions that fail on new examples.
Two useful terms
Split: a question that divides examples. Leaf: a final node that provides a prediction.
Build your understanding
A decision tree predicts by applying a sequence of feature-based splits. It is easy to visualise when small, which makes it a useful teaching model. Deep trees can create tiny leaves that memorise noise. Tree rules describe associations in the fitted dataset, not universal laws.
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