AI, Deep Learning, Clustering, Python.
centroids, where K represents the desired number of clusters. The algorithm then iteratively assigns each data point to the nearest centroid and recalculates the centroid’s position based on the mean of the data points assigned to it. This process continues until convergence, where the centroids