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This Decision Tree in the Machine Learning tutorial will help you understand all the basics of the Decision Tree and how the Decision Tree algorithm works. In the end, we will implement a Decision Tree algorithm in Python on loan payment prediction. This Decision Tree tutorial is ideal for both beginners as well as professionals who want to learn Machine Learning Algorithms.

Below topics are covered in this Decision Tree Algorithm Tutorial:
0. Intro (0:00)
1. What is Machine Learning? ( 02:25 )
2. Types of Machine Learning? ( 03:27 )
3. Problems in Machine Learning ( 04:43 )
4. What is a Decision Tree? ( 06:29 )
5. What are the problems a Decision Tree Solves? ( 07:11 )
6. Advantages of Decision Tree ( 07:54 )
7. How does Decision Tree Work? ( 10:55 )
8. Use Case - Loan Repayment Prediction ( 14:32 )

Dataset Link - https://drive.google.com/drive/folders/1JybOOdRsMYH0z8fehVuFNLhZ60UsO-4W

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What is a Decision Tree Algorithm?
A Decision Tree is a supervised machine learning algorithm for solving classification problems. Generally, a decision tree is drawn upside down with its root at the top and it is known as the Top-Down Approach. Decision trees are used for handling non-linear data sets effectively. The decision tree tool is used in real life in many areas, such as engineering, civil planning, law, and business.

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