In this tutorial on 'Machine Learning Algorithm', you will learn about Random Forest Algorithm.
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Timestamps
0:30 Why Random Forest?
0:47 What is Random Forest?
1:42 What is a Decision Tree?
2:00 How is a Decision tree constructed?
2:34 Random forest important terms
3:20 Working of Random Forest
3:40 Random Sampling with Replacement
4:21 Working of Random Forest
6:12 Advantages of Random Forest

Random forest is constructed using multiple decision trees and the final decision is obtained by majority votes of decision trees.
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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