39. Decision Trees

Описание: 📌 Video Description

Decision Trees are intuitive and powerful algorithms used in data science and machine learning for both classification and regression tasks. In this video, we explain how decision trees work using a tree-shaped structure that mimics human decision-making.

You’ll learn how internal nodes represent tests or conditions on features, branches represent outcomes of those tests, and leaf nodes represent final decisions or predictions. Decision trees are popular because they are easy to understand, visualize, and interpret, making them ideal for explaining model decisions to non-technical audiences.

This lesson builds strong intuition behind how decision trees split data and make predictions.

🎯 What You’ll Learn in This Video

What a decision tree is

Tree structure explained: nodes, branches, and leaves

Role of internal nodes as decision tests

Role of leaf nodes as final decisions

How decision trees make predictions

Advantages and limitations of decision trees

Real-world use cases of decision trees

👨‍💻 Who This Video Is For

Data science and machine learning beginners

Students preparing for exams

Data analysts and business intelligence professionals

Anyone learning interpretable ML models

🔑 Keywords (SEO)

Decision Trees, Decision Tree Algorithm, Machine Learning Trees, Classification Trees, Tree Based Models, Data Science Fundamentals, Interpretable Machine Learning, Learn Decision Trees

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📌 Hashtags

#DecisionTrees #MachineLearning #DataScience #TreeBasedModels #Classification #LearnDataScience #TechFundamentals