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There is a lot of activity on leveraging Scala's expressiveness and ecosystem for large-scale learning tasks. This paper introduces three projects that are conducted in the context of the Scala team. By focusing on the used language features, the authors attempt to distill commonalities among the discussed tools and frameworks; at the same time, this allows one to differentiate the tools and frameworks based on their implementation approach. They hope that a categorization of language features according to the level of required Scala experience helps end users, ML experts, and system builders to find features and tools that satisfy their particular needs.
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