Our video series simplifies federated machine learning. These videos cover the FEDn framework, address key challenges, and emphasize the importance of understanding distributed setups for building reliable models. Perfect for learners and experts alike.
Featured video
This video underscores the importance of understanding the distributed setup used in training federated machine learning models. Without this information, any reports on the model remain incomplete. Key details, including the number of participating clients, data distribution, communication costs, and the total time required for training, are essential for ensuring transparency and building confidence in the model’s effectiveness.
Cross-device federated machine learning
Federated machine learning for cross-device use cases is a critical yet complex research area. It demands a deep understanding of machine learning processes, distributed computing, and the unique constraints of edge devices. One of the major challenges lies in creating an experimental environment that accurately simulates real-world conditions.
Developing Applications with FEDn APIs
This video is part of our series dedicated to addressing challenges in federated machine learning and demonstrating how the FEDn framework effectively resolves them. Here, we focus on the importance of API-based communication and explore its practical benefits for real-world federated learning scenarios.
Mastering the compute package
This video provides an in-depth look at the compute package, a crucial element of the FEDn framework that governs the training execution process on the client side. Building on our previous video, “Getting Started with FEDn,” this exploration dives into how the compute package functions within the broader framework.
Getting started with FEDn
This video provides a comprehensive overview of the FEDn framework, guiding you through three essential areas: where to access detailed resources and documentation, a step-by-step tutorial for launching your first federated machine learning project, and an introduction to key terminologies used within the framework to help you better understand and navigate the system.
Federated learning explained
This video introduces the fundamental concept of federated machine learning in a straightforward manner, avoiding technical jargon. While federated learning is widely known for its privacy-preserving features, this video goes beyond that to showcase other significant advantages that could revolutionize various industries, illustrated through a clear and relatable example.
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