Step-by-Step Guide to Random Forest in Machine Learning | PART 1 | AI ML Course By Srinivasan R 

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This tutorial will dive deep into Random Forest classification and Bootstrap Aggregation (Bagging)!
Whether you're a beginner or someone looking to enhance your machine-learning skills, this video will guide you through:
The basic concepts behind Random Forests
How bagging works to improve model accuracy
Why Random Forest is one of the most powerful and widely used algorithms in data science
We'll break down key concepts with real-life examples, ensuring you understand how Random Forest helps in tasks like medical diagnosis, fraud detection, and recommendation systems. By the end, you'll be ready to implement Random Forests in your own machine-learning projects and boost the performance of your models!
What you'll learn:
Introduction to Random Forest and Bagging
How Random Forest reduces overfitting and increases accuracy
Practical use cases in real-world applications
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