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Unsure about classification vs. clustering? Classification sorts data into existing categories, like spam filtering or image recognition. Clustering uncovers hidden groups, useful for customer segmentation or anomaly detection. Both techniques power data science! Learn when to use each to unlock the secrets within your data.<\/span><\/p>\n Machine Learning is a subset of Artificial Intelligence and Computer Science that uses data and algorithms to imitate human learning and improve accuracy. Being an important component of Data Science, the use of statistical methods is crucial in training algorithms to make classifications.\u00a0<\/span><\/p>\n Certainly, these predictions and classifications help in uncovering valuable insights in data mining projects. <\/span>ML algorithms<\/span><\/a> fall into various categories, generally characterised as Regression, Clustering, and Classification.\u00a0<\/span><\/p>\n While Classification is an example of a directed Machine Learning technique, Clustering is an unsupervised Machine Learning algorithm. The blog will take you on a journey to learn more about these algorithms and unfold a comparison of Classification vs. Clustering.<\/span><\/p>\n