
DMTK provides a parameter server based framework for training machine learning models on big data with numbers of machines. It is currently a standard C++ library and provides a series of friendly programming interfaces. With such easy-to-use APIs, machine learning researchers and practitioners do not need to worry about the system routine issues such as distributed model storage and operation, inter-process and inter-thread communication, multi-threading management, and so on. Instead, they are able to focus on the core machine learning logics: data, model, and training.
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