In this paper, we present Fedlearn-Algo, an open-source privacy preserving
machine learning platform. We use this platform to demonstrate our research and
development results on privacy preserving machine learning algorithms. As the
first batch of novel FL algorithm examples, we release vertical federated
kernel binary classification model and vertical federated random forest model.
They have been tested to be more efficient than existing vertical federated
learning models in our practice. Besides the novel FL algorithm examples, we
also release a machine communication module. The uniform data transfer
interface supports transfering widely used data formats between machines. We
will maintain this platform by adding more functional modules and algorithm
examples.

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