Reinforcement Learning is a branch of AI that focuses on training agents to make decisions through trial and error in a specific environment. By employing positive reinforcement and punishments, businesses can teach machines to optimise actions and learn from rewards, enabling autonomous decision-making in dynamic situations.
Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated…