Random Forest Regression (Part 2) | How It Works & Python Implementation | Machine Learning
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Random Forest Regression (Part 2) | How It Works & Python Implementation | Machine Learning
33 просмотра · 11 дн. назад
jaybrainwave
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33 просмотра · 11 дн. назад
Random Forest Regression (Part 2) | How It Works & Python Implementation | Machine Learning
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🌳 Random Forest Regression Part 2 | How It Works & Python Implementation | Machine Learning
In this video, we will learn how Random Forest Regression works and how to implement it practically using Python and Scikit-Learn.
Random Forest Regression is a powerful supervised machine learning algorithm that uses multiple Decision Trees to make accurate numerical predictions.
📌 Topics Covered in This Video:
How Random Forest Regression works
Understanding Ensemble Learning
How multiple Decision Trees work together
Bootstrap Sampling
Random Feature Selection
Prediction using Random Forest
Python implementation using Scikit-Learn
Model Training and Prediction
Model Evaluation using MAE, MSE and R² Score
💻 Technologies Used:
Python
NumPy
Pandas
Matplotlib
Scikit-Learn
Jupyter Notebook
🎯 Who Should Watch?
Beginners in Machine Learning
Data Science Students
AI/ML Engineer Aspirants
Anyone learning Python and Machine Learning
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