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How do you go about choosing the optimal number of clusters for K-means algorithm without overfitting?

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Interview question asked to Machine Learning Engineers interviewing at Adyen, McAfee, SAP and others: How do you go about choosing the optimal number of clusters for K-means algorithm without overfitting?.