Random Forests

Introduction to Random Forests 🌿

Random Forests are powerful machine learning models capable of performing both classification and regression tasks. They operate by constructing multiple decision trees during training time and outputting the mode or mean prediction of the individual trees.

Explore more about Random Forests on Wikipedia.

Why Use Random Forests? 🤔

• Handle large datasets with higher dimensionality.
• Effective at preventing overfitting.
• Works well with both categorical and continuous values.

Hands-On: Implementing Random Forests 🛠️

Get your hands dirty with code and create your own Random Forest model using Python's scikit-learn library. Check out this amazing tutorial on creating Random Forests from scratch.

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