Docker for Data Science
Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server
Ranked #22 in Docker
Learn Docker "infrastructure as code" technology to define a system for performing standard but non-trivial data tasks on medium- to large-scale data sets, using Jupyter as the master controller.
It is not uncommon for a real-world data set to fail to be easily managed. The set may not fit well into access memory or may require prohibitively long processing. These are significant challenges to skilled software engineers and they can render the standard Jupyter system unusable.
As a solution to this problem, Docker for Data Science proposes using Docker. You will learn... more
It is not uncommon for a real-world data set to fail to be easily managed. The set may not fit well into access memory or may require prohibitively long processing. These are significant challenges to skilled software engineers and they can render the standard Jupyter system unusable.
As a solution to this problem, Docker for Data Science proposes using Docker. You will learn... more
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