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A Decision Tree is like a flowchart that helps make decisions.
It starts with a main question (the root) and branches out based on answers.
Each branch leads to more questions or decisions (nodes) until it reaches a final decision (leaf).
For example, if deciding whether to buy an umbrella:
Itβs simple, like following "if-then" rules step by step!

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In a Decision Tree, mathematics is used to decide how to split data at each step.
Measures the "messiness" of data.
Lower entropy means data is more organized.

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https://github.com/mdntarif/ML_Decision_Tree/blob/main/ML_Decision_Tree.ipynb