Answer / Meenu

k-means clustering is a popular unsupervised learning algorithm used for grouping data points into K clusters. The objective is to minimize the sum of distances between each data point and its assigned cluster center (also known as mean). In simple terms, k-means works by iteratively assigning data points to one of K predefined groups or clusters, based on their similarity, and then updating the cluster centers based on the newly assigned data points.

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