MLpods aims at facilitate the process of data munging, pipelining, model building and testing in a Data Science project. It is heavily inspired by various examples of usage of docker. While it was built during the process of Data Science projects, these tools are planed to also serve general purposes.
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MLpods quickly spin up a container in the cloud (not yet released)
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FunPod functional container that is called on-demand to handle a request. heavily inspired by the funker project, see examples in
tests/