Past Meetup

Introduction to Dask: a lightweight library for distributed computing in Python

This Meetup is past

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We invite you to join us for our July monthly meeting. Our speaker will be Jesse Daniel. Jesse is a Senior BI Consultant at Decentrix and also an Adjunct Professor of Business Information and Analytics at the University of Denver.

Jesse will be providing us with an overview of Dask. Dask is a flexible parallel computing library for analytics that enables data munging, exploration, visualization, and machine learning on larger-than-RAM datasets. The Dask API is modeled after well-known data structures in Python, such as Pandas DataFrames, NumPy arrays, and bags, making it very easy to work with. Dask supports the full benefits of out-of-core execution, distributed scheduling, and clustering all without the overhead of setting up and maintaining YARN or Spark, and can be installed easily using pip.

Jesse will demonstrate common use-cases with Dask, as well as a side-by-side comparison with Pandas.

To expedite the check-in process at Galvanize, please also enroll on the Eventbrite page by clicking here (https://www.eventbrite.com/e/pydata-presents-introduction-to-dask-a-lightweight-library-for-distributed-computing-in-python-tickets-35061107717).

We hope to see you there!