Random Forest Explained | Random Forest Algorithm in Machine Learning | Data Science | Intellipaat
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If you're interested in machine learning, you've probably heard of "Random Forest". In this video on Random Forest Algorithm in Machine Learning, we'll explore what Random Forest is, how it works, and how it can be used in various applications.
Random Forest is a popular machine learning algorithm that is used for classification, regression, and feature selection tasks. It is a type of ensemble learning method that combines multiple decision trees to make more accurate predictions. Each decision tree is trained on a subset of the data and a random subset of features, which helps to prevent overfitting and improve generalization.
Whether you're new to machine learning or an experienced practitioner, this video will provide a comprehensive overview of Random Forest and its applications. So sit back, relax, and let's dive into the world of Random Forest!
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🔵 Following topics are covered in this session:
0:00 - Introduction
1:19 - What is Random Forest?
3:23 - Concept of Decision Tree
5:34 - Working Details of Random Forest Algorithms
12:16 - Advantages & Disadvantages of Random Forest Algorithms
16:55 - Hands-On Demo for Random Forest
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