Themes
In Data Science, themes refer to the underlying patterns or topics that emerge from the analysis of a dataset. These themes can be identified through various techniques such as clustering, topic modeling, and sentiment analysis. Themes can provide insights into the underlying structure of the data and can be used to develop predictive models or to identify areas for further investigation. Themes can also be used to summarize large amounts of data and to communicate findings to stakeholders in a clear and concise manner.
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