What is Federated Learning(FL)? Techniques & Benefits in 2021

Federated learning is a machine learning method that enables machine learning models obtain experience from different data sets located in different sites (e.g. This allows personal data to remain in local sites, reducing possibility of personal data breaches. Federated learning is used to train other machine learning algorithms by using multiple local datasets without exchanging data. This allows companies to create a shared global model without putting training data in a central location. In machine learning, there are 2 steps, training and inference.