In today’s world when there is a so much data to deal with and with this big data it has become a challenging task to keep to data secure and provide a good computing speed. So, to overcome such issues federated learning (FL) was introduced. Federated learning approach can be useful in following ways:
FL approach helps us to get lower latency rate and a good processing power.
To get a better privacy, data security, and data access right at user end.
FL is a collaborative based learning and also a decentralised learning model.
Training algorithms on multiple private local datasets.
Exchanging parameters. And helps to reach global model accuracy.