Summary
This chapter focused on clustering and how it could be used to group your data into separate areas. Creating these areas made it easier to understand our data points. Through visualization like heat maps, word clouds, and more, you were given the insight that data benefits from being shown in different ways. You also saw how the clustering process helped identify outliers, that is, data that vastly differs and can’t easily be assigned to any one cluster. For the ChatGPT and prompting part, you saw how setting a high-level context describing the dataset helped generate a suitable set of steps you could follow from top to bottom. The same high-level context also helped ChatGPT recommend a clustering algorithm.
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