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We'll begin by talking about the different pattern in tooling for Python when doing data science- this can be useful for all Pythonistas. We'll cover Jupyter, Anaconda, Numpy and Numpy arrays and how they underlie a host of other libraries like Scipy, Pandas, and SKLearn. Then we'll work through analysis with a built-in data set.

Speaker: Nick / @nohmapp

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