15.6 Case Study: Unsupervised Machine Learning, Part 1—Dimensionality Reduction
In our data science presentations, we’ve focused on getting to know your data. Unsupervised machine learning and visualization can help you do this by finding patterns and relationships among unlabeled samples.
For datasets like the univariate time series we used earlier in this chapter, visualizing the data is easy. In that case, we had two variables—date and temperature—so we plotted the data in two dimensions with one variable along each axis. Using Matplotlib, Seaborn and other visualization libraries, you also can plot datasets with three variables using 3D visualizations. But how do you visualize data with more than three dimensions? For example, in the Digits ...
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