Random Forest Algorithm – Random Forest Explained | Random Forest in Machine Learning | Simplilearn

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This Random Forest Algorithm tutorial will explain how the Random Forest algorithm works. By the end of this video, you will be able to understand what is Machine Learning, what is a Classification problem, applications of Random Forest, why we need Random Forest, how it works with simple examples, and how to implement a Random Forest algorithm in Machine Learning. This video is a part of the Machine Learning with Python Series.

Below are the topics covered in this Random Forest Algorithm tutorial:
00:00 – 02:08 Applications of Random Forest Algorithm
02:08 – 02:59 Agenda
02:59 – 04:07 Classification Algorithms
04:07 – 05:36 Why Random Forest?
05:36 – 06:40 What is Random Forest Algorithm?
06:40 – 11:01 What is a Decision Tree?
11:01 – 14:18 How does the Decision Tree algorithm work?
14:18 – 17:27 How does the Random Forest algorithm work?
17:27 – 45:34 Use Case – IRIS Flower Analysis using Python

Dataset Link – https://drive.google.com/drive/folders/1MQ5Nnhj3gs6TcIl0fcKP_AfOh8EMDB42

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#RandomForestAlgorithm #MachineLearningAlgorithm #DataScience #SimplilearnMachineLearning #MachineLearningCourse #Simplilearn

What is Random Forest Algorithm?
The random forest algorithm is a supervised machine learning algorithm that takes randomly selected data and creates different decision trees. It then makes the collection of votes from trees to decide the class of the test object.

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