Data Science Workflows Using Docker Containers

May 7, 2018 · Chicago, United States of America

Containerization technologies such as Docker enable software to run across various computing environments. Data Science requires auditable workflows where we can easily share and reproduce results. Docker is a useful tool that we can use to package libraries, code, and data into a single image. This talk will cover the basics of Docker; discuss how containers fit into Data Science workflows; and provide a quick-start guide that can be used as a template to create a shareable Docker image! Learn how to leverage the power of Docker without having to worry about the underlying details of the technology.

Aly Sivji is a Mathematician / Software Engineer at a healthcare startup in Chicago and a part-time grad student at Northwestern University studying Medical Informatics. He is passionate about Python, cycling, and improving healthcare delivery models using information technology.

6:00 p.m - 6:30 p.m is time for social. Seminar will start at 6:30 p.m.
Please note the office security needs to check your ID for entry. Thanks for your understanding.

Our Sponsor: Arity ( )

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  • PyData Chicago

    PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to)

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