👉 The Ef Project (Efficient Federated Learning) is an initiative focused on enhancing the efficiency and scalability of federated learning, a machine learning approach that trains models across multiple decentralized devices or servers holding local data samples without exchanging them. Ef Project aims to address key challenges such as communication overhead, computational constraints, and privacy concerns by developing techniques like model compression, federated averaging with adaptive learning rates, and secure aggregation methods. These innovations enable more efficient collaboration among devices, making federated learning viable for a broader range of applications, from IoT devices to healthcare and finance, where data privacy and resource limitations are critical.