Date(s) - 12/06/2018
2:00 pm - 3:00 pm


3910 15th Ave NE
Seattle WA

“Scalable analysis in Python with Dask”


Dask is a library designed to parallelize other popular libraries in the scientific Python ecosystem like Numpy, Pandas, and Scikit-Learn. In this talk we’ll discuss Dask from three perspectives:

1.  As a user: and how Dask is used today to take traditional scientific analysis workloads from laptops to clusters using familiar tools
2.  As a computer Scientist: and the underlying technologies of dynamic task scheduling
3.  As a community member: and the benefits and challenges of parallelizing an existing software ecosystems
If you’d like to learn more before the talk or try things out we recommend the following links: and


A photo of Matthew Rocklin
Matthew Rocklin is an open source software developer in the Python ecosystem focused on parallel computing. He contributes to many of the PyData libraries, but primarily works on Dask, a library for scalable computing. Matthew holds a bachelor’s degree from UC Berkeley in physics and mathematics, and a PhD in computer science from the University of Chicago.