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Published on
Given at PyDataSV 2014
In machine learning, clustering is a good way to explore your data and pull out patterns and relationships. Scikit-learn has some great clustering functionality, including the k-means clustering algorithm, which is among the easiest to understand. Let's take an in-depth look at k-means clustering and how to use it. This mini-tutorial/talk will cover what sort of problems k-means clustering is good at solving, how the algorithm works, how to choose k, how to tune the algorithm's parameters, and how to implement it on a set of data.
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