How to get started with data science in containers

blog.kaggle.com

The biggest impact on data science right now is not coming from a new algorithm or statistical method. It’s coming from Docker containers. Containers solve a bunch of tough problems simultaneously: they make it easy to use libraries with complicated setups; they make your output reproducible; they make it easier to share your work; and they can take the pain out of the Python data science stack.

We use Docker containers at the heart of Kaggle Scripts. Playing around with Scripts can give you a sense of what you can do with data science containers.

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