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Federated learning is used for distributed training of machine learning algorithms on multiple devices without exchanging training data. The video discusses the History of Federated Learning, different Architectures, the challenges associated with using the platform, as well as the potential future prospects for the technology. The speaker also explained the framework "Flower" which is an open-source framework for Federated Learning.
Maria Boerner has a Ph.D. in physics and an academic background in data analysis and processing. She worked at the world's largest Particle Colliders CERN and DESY and managed AI projects at for Porsche, PwC and Daimler.
Federated learning is used for distributed training of machine learning algorithms on multiple devices without exchanging training data. The video discusses the History of Federated Learning, different Architectures, the challenges associated with using the platform, as well as the potential future prospects for the technology. The speaker also explained the framework "Flower" which is an open-source framework for Federated Learning.
Maria Boerner has a Ph.D. in physics and an academic background in data analysis and processing. She worked at the world's largest Particle Colliders CERN and DESY and managed AI projects at for Porsche, PwC and Daimler.