Transfer learning vs federated learning: A comparative analysis

Think of the things artificial intelligence and machine learning have accomplished in the last few years– real-time translations, outperforming humans at board games, drug discovery etc. Transfer learning, federated learning, reinforcement learning, self-supervised learning etc., are the cutting-edge techniques that made these milestones possible. While transfer learning is an old machine learning technique, federated learning was introduced in 2017 by Google. Deep learning models need huge swathes of labelled data to be trained on to learn and work effectively. The process is also time-consuming. Transfer learning can help tackle these challenges.