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In this video on Decision Tree Machine Learning, we will dive into one of the most popular and powerful algorithms in machine learning: Decision Trees.

Decision Trees are widely used in various industries to solve classification and regression problems. They are easy to interpret and visualize, making them a great tool for understanding the decision-making process in machine learning models.

In this tutorial, we will start with the basics of Decision Trees, such as what they are, how they work, and how to build a tree model from scratch. Then, we will explore some advanced techniques, including pruning, ensemble methods, and boosting.

We will also discuss some real-world applications of Decision Trees, such as fraud detection, customer segmentation, and medical diagnosis.

By the end of this video, you will have a solid understanding of Decision Trees and how they can be applied to solve real-world problems. So, whether you're a beginner or an experienced data scientist, this video is perfect for anyone looking to learn more about Decision Trees in machine learning.

So, grab a coffee, sit back, and let's dive into the fascinating world of Decision Trees!

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Following topics are covered in this session:
0:00 - Introduction
0:56 - Introduction to Decision Tree
6:54 - Important Terms related to Decision Tree
13:39 - Hands-On Implementation of Decision Tree Algorithm

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