Answered step-by-stepQUESTION 1 : In few words, give your substantive comment on...
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In few words, give your substantive comment on Neisha's post below:
K means clustering is a popular machine learning algorithm. It's an unsupervised method because it starts without labels and then forms and labels groups itself. K means clustering is not a supervised learning method because it does not attempt to predict existing or known group labels.
The K means clustering algorithm divides a set of n observations into k clusters. Use K means clustering when you don't have existing group labels and want to assign similar data points to the number of groups you specify (K). K means clustering forms the groups in a manner that minimizes the variances between the data points and the cluster's centroid.
Imagine you have a large dataset of observations, but there is no grouping information or labels for the data points. Use K means clustering to generate groups comprised of observations with similar characteristics. For example, if you have customer data, you might want to create sets of similar customers and then target each group with different types of marketing.
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sectetur adipiscing elit. Nam lacinia pulvinar tortor nec facilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, dapibus a molestie consesectetur adipiscing elit. Nam lacinia pulvinar tortor nec facilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, dapibus a molestie consequat, ultrices ac magna. Fusce dui lectus, congue vel laoreet ac, dictum vitae odio. Donec al
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sectetur adipiscing elit. Nsectetur adipiscing elit. Nam lacinia pulvinar tortor nec facilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, dapibus a molestie consequat, ultrices ac magna. Fusce dui lectus, congue vel laoreet ac, dictum vitae odio.
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sectetur adipiscing elit. Nam lacinia pulvinar tortor nec facilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, dapibus a molestie consequat, ultrices ac magna. Fusce dui lectus, congue vel laoreet ac, dictum vitae odio.
sectetusectetur adipiscing elit. Nam lacinia pulvinar tortor nec facilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, dapibus a molestie consequat, ultrices ac magna. Fusce dui lectus, congue vel laoreet ac, dictum vitae odio. Donec aliquet. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nam lacinia pulvinar tortor nec facilisis. Pellentesque dapibus efficitur laoreet. Nam risus ante, dapibus a molestie consequat, ultrices ac magna. Fusce dui lectus, congue vel laoreet ac, dictum vitae odio. Donec aliquet
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