Scaling Python with Dask

Data scientists love the wealth of awesome capabilities offered by Python packages like Numpy, Pandas, and scikit-learn. However, these capabilities historically have been limited to data that can fit on a single machine.

Until now.

In Scaling Python with Dask, Lead Dask Developer Matt Rocklin will show how simple Dask makes scaling beyond a single machine while supporting the packages you’re already using.

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Matthew Rocklin, Lead Dask Developer

Matt is an open source software developer at Anaconda focusing on efficient computation and parallel computing, primarily within the Python ecosystem. He has contributed to many of the PyData libraries and is the Lead Developer of the Dask library for parallel computing. Matt holds a PhD in computer science from the University of Chicago, where he focused on numerical linear algebra, task scheduling, and computer algebra.

With over 15 million users, Anaconda is the world’s most popular Python data science platform. Anaconda, Inc. continues to lead open source projects like Anaconda, NumPy and SciPy that form the foundation of modern data science. Anaconda’s flagship product, Anaconda Enterprise, allows organizations to secure, govern, scale and extend Anaconda to deliver actionable insights that drive businesses and industries forward.

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