Deep Dive into Dask with Matthew Rocklin @Uber

On Tuesday January 31, please join us for a deep dive into Dask, Python's powerful and flexible paralleling computing library. The session will be led by Dask's lead developer, Matthew Rocklin.

Event Summary:

The data science Python ecosystem (NumPy, Pandas, Scikit-Learn) are efficient and intuitive for advanced analytics workloads. Unfortunately, these tools are restricted to data that fits into memory and runs on a single core.

Dask is a parallel computing library that complements the Python ecosystem by providing a distributed parallel framework for high performance task scheduling. Dask parallelizes NumPy, Pandas, and Scikit-Learn workloads on multi-core computers or distributed clusters. This effort was done in collaboration with those core development communities and has lead to a seamless big data experience for Python users for data analysis and complex analytics.

This talk will describe the basic architecture of Dask, classes of applications in which it is commonly useful, and provide rich examples of its use.

For more information see: http://dask.pydata.org/en/latest/

Speaker Biography:

Matthew is an open source software developer focusing on efficient computation and parallel computing, primarily within the Python ecosystem. He has contributed to many of the PyData libraries and today works on Dask (http://dask.pydata.org/) a framework for parallel computing. Matthew holds a PhD in computer science from the University of Chicago where he focused on numerical linear algebra, task scheduling, and computer algebra.

Matthew lives in Brooklyn, NY and is employed by Continuum Analytics.

Website: http://matthewrocklin.com (http://matthewrocklin.com/)

Blog: http://matthewrocklin.com/blog

Dask: http://dask.pydata.org/

Sponsors:

A big thanks to the folks at Uber for offering their space to host this event!