🧠 *Ensemble Learning in AI* 🧠

Discover the power of combining multiple models for superior performance! 🚀✨

1. Bagging 👜:
Boost accuracy by training multiple models on random subsets of data and averaging their predictions.
Key technique: Random Forests 🌳

2. Boosting 🔋:
Sequentially build models that correct errors of the previous ones, enhancing overall performance.
Key technique: AdaBoost ⚡, Gradient Boosting 🌟

3. Stacking 📚:
Train multiple models and combine them using a meta-model for the final prediction.
Key technique: Stacked Generalization 🏆

Unlock the full potential of your AI models with ensemble learning! 🔓💡

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