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‘Dimensionality Reduction’ Interview Questions

What is dimensionality reduction?

What is Principal Component Analysis (PCA), and how does it differ from clustering?

What is Kernel PCA?

What is Independent Component Analysis (ICA), and how is it distinguished from PCA?

What is Factor Analysis, and how does it differ from PCA?

How does T-distributed Stochastic Neighbor Embedding (T-SNE) work at a high level?

How does T-SNE compare to PCA?

What is Random Projection? Discuss its advantages and disadvantages?

When to use PCA vs Random Projection?

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