SciPy (pronounced sigh pi) adds a layer to NumPy that wraps common scientific and statistical applications on top of the more purely mathematical constructs of NumPy. SciPy provides higher-level functions for manipulating and visualizing data, and it is especially useful when using Python interactively. SciPy is organized into sub-packages covering different scientific computing applications. A list of the packages most relevant to ML and their functions appear as follows:




This contains two sub-packages:

cluster.vq for K-means clustering and vector quantization.

cluster.hierachy for hierarchical and agglomerative clustering, which is useful for distance matrices, calculating statistics on clusters, as ...

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