How does the Decision tree work in Machine Learning? In this tutorial, you will learn about Decision Tree Algorithm in Machine Learning and Important Terms of Decision Tree ( Entropy, Information Gain, Root Node, Leaf Node).
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Timestamps
0:30 Decision Tree
1:15 Problems that Decision Tree can solve
1:51 Decision Tree- Important Terms
2:56 How does a Decision Tree Work?
7:12 Advantages and Disadvantages of Decision Tree

Decision tree is a tree shaped diagram used to determine a course of action. This tutorial explains decision tree in machine learning and its implementation.
In this series you will learn all types of Machine Learning Algorithms, Supervised Learning, Unsupervised Learning, Reinforcement Learning, KNN, Decision Tree, Linear Regression, Support Vector Machine, Random Forest, Naive Bayes, Logistic regression, K means clustering, Hierarchical clustering, Anomaly detection, Q learning, Deep Q Networks, and more.

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