Intro on Using Python for Big Data

Hannah Aizenman

Intro on Using Python for Big Data

An overview of the Python scientific computing stack, with a focus on working with very large datasets. I'll try to introduce the most widely used libraries for scientific computing, Numpy and Scipy, discuss techniques for using them with big data, and touch on some of the machine learning techniques (and possibly libraries) for reducing large data into something manageable. Then I'll go over how to make some of the most common data visualization tasks (plotting a time-series or mapped data using matplotlib) dynamic and web-based.

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About Hannah Aizenman:
Hannah Aizenman is working on a PhD in Computer Science at The Graduate Center, CUNY. Her research is in using machine learning to make sense of and visualize large, mostly climate, datasets, and she's spent the past two summers writing related web apps. Hannah's also a sometime NYLUG workshop/hacking society coordinator.

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  • Robert M.

    October 21, 2012

  • nick c.

    awesome: Hannah * her slides = inspiration. i went home and plotted graphs on matplotlib.

    September 19, 2012

  • James B.

    Good presentation, it was indeed an Intro but gave a lot of jumping off points for further study. And the presenter was knowledgeable, handled most questions very well.

    September 14, 2012

  • Gregg C L.

    Excellent.

    September 13, 2012

  • David J.

    cannot come, but very interested

    September 8, 2012

  • nick c.

    yaaahoooo, thanks for letting me in.

    September 7, 2012

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