Decision Trees Explained Simply | How Machines Make Decisions | Machine Learning

Описание: Have you ever wondered how your streaming app knows what to recommend—or how a bank can approve a loan in seconds?

A lot of the time, the answer is Decision Trees.

In this video, we break down Decision Trees in the simplest way possible by comparing them to something you already do every day: making decisions by asking yes/no questions.

Instead of diving into code or complex math, we focus on intuition, visuals, and real-life examples so the logic instantly makes sense.

🔍 What you’ll learn in this video:

What a Decision Tree really is (a flowchart of decisions)

How machines break big problems into simple yes/no questions

The structure of a decision tree:

🌱 Root node

🌿 Decision nodes

🍃 Leaf nodes

Step-by-step walkthrough of a real decision tree example

How Decision Trees work for:

🏷️ Classification (spam vs not spam, fit vs unfit)

📈 Regression (predicting numbers like prices or temperatures)

Why Decision Trees are popular in banking, healthcare, and recommendations

The biggest advantage of Decision Trees: transparency

We also explain why Decision Trees are often called “glass box” models—because unlike black-box AI, you can clearly see why a decision was made.

🎯 Perfect for:
✅ Machine Learning beginners
✅ Students & self-learners
✅ Anyone curious about how AI makes decisions
✅ Viewers who want intuition before algorithms

By the end of this video, you’ll be able to spot Decision Tree logic everywhere—from recommendations to credit approvals—and understand how machines think step by step.

👉 Next video: Where Decision Trees struggle—and how more advanced models build on them 🌲🌲

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