Abstract: There is provided a method of federated machine learning using at least one processor, the method including: transmitting a current global machine learning model to each of a plurality of data sources; receiving a plurality of training updates from the plurality of data sources, respectively, each of the plurality of training updates being generated by the respective data source in response to the global machine learning model received; and updating the current global machine learning model based on the plurality of training updates received and a plurality of data quality parameters associated with the plurality of data sources, respectively, to generate an updated global machine learning model. There is also provided a corresponding server for federated machine learning.