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

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.

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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!