Answer / Munazir Hussain

Dimensionality Reduction is a technique used to reduce the number of random variables under consideration, while retaining the essential information. This is useful in machine learning as it can alleviate the curse of dimensionality by minimizing overfitting, speeding up training times, and improving model interpretability.

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