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Julia for Data Science by Zacharias Voulgaris PhD

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CHAPTER 10: Unsupervised Machine Learning

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One of the fundamentals of data science is finding patterns in the data at hand. As you may remember from Chapter 5, this is accomplished mainly during the data exploration part of the pipeline. Although the various statistical methods and plots yield much useful insight, sometimes we must employ a more sophisticated approach. This is particularly useful if we have certain expectations about the data (such as different groups or patterns that should exist) and wish to explore them further.

This lends itself to what is known as unsupervised learning: the kind of machine learning where labels are unknown ...

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