An Introduction to Federated Learning: Challenges and Applications - viso.ai

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Viso Suite is the all-in-one solution for teams to build, deliver, scale computer vision applications. Viso Suite is the world’s only end-to-end computer vision platform. Request a demo. Federated learning is used for distributed training of machine learning algorithms on multiple edge devices without exchanging training data. Therefore, Federated learning introduces a new learning paradigm where statistical methods are trained at the edge in distributed networks. Read about the unique properties and associated challenges of federated learning; we will cover the following: About us: Viso.ai provides the leading end-to-end Computer Vision Platform Viso Suite. Global organizations use it to develop, deploy and scale distributed Computer Vision Applications that run at the Edge. Get a personal demo. Today, an immense number of connected devices, including mobile devices, wearables, and autonomous vehicles, generate massive amounts of data (Big Data). Due to the fast-growing computational

Subscribe to the viso blog Stay connected with viso.ai and receive new blog posts straight to your inbox. Subscribe We use federated learning in the distributed model training on multiple edge devices without exchanging training data. Therefore, federated learning introduces a learning paradigm where statistical methods are trained at the edge in distributed networks. Why We Need Federated Learning Computer Vision Builder Bring a new AI vision application to life. Turn ideas into computer vision apps — no coding needed. Big Data and Edge-Computing Trend Connected devices, including…

An Introduction to Federated Learning: Challenges and Applications - viso.ai

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