What is dimensionality reduction, and why is it important in machine learning?

Instruction: Discuss the concept of dimensionality reduction, its importance, and common methods used.

Context: The question aims to evaluate the candidate's knowledge on reducing the number of random variables under consideration, and techniques such as PCA (Principal Component Analysis).

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The way I'd explain it in an interview is this: Dimensionality reduction is the process of representing the data with fewer features while trying to keep the signal that matters. Sometimes that means projecting the data into a lower-dimensional space, and...

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