Ai+ Training

The rapidly evolving world of machine learning is posing new challenges for data privacy and intellectual property protection. This insightful talk delves into the concept of Federated Learning, a transformative approach that empowers organizations to collaborate securely while preserving privacy and safeguarding intellectual property. By harnessing the capabilities of Azure Machine Learning and NVIDIA Flare, this talk illustrates how this technology can influence the future of AI development. 

This engaging session starts by elaborating on the critical role of Federated Learning in today's data-driven landscape. The groundbreaking idea will be explored that allows multiple organizations to train machine learning models on decentralized data, providing valuable insights without exposing sensitive information. By leveraging this approach, businesses can unlock the true potential of collaborative AI while maintaining robust security standards. 

Following the introduction, there will be an in-depth walkthrough of a hands-on demo that showcases the power of Federated Learning. Using a real-world medical imaging use case, it shows how Azure Machine Learning and NVIDIA Flare can be combined to facilitate collaboration between organizations, enhance model performance, and contribute to the greater good of medical research.

Additional learning resources for you: 

AI Show | Federated Learning with Azure Machine Learning  https://aka.ms/AIShow/FederatedLearning 

Azure Machine Learning | Documentation https://aka.ms/AzureMachineLearning/Docs Azure 

Machine Learning | Learning Path https://aka.ms/AzureML/LearningPath

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