🔹 Federated Learning as Locally Weighted Learning! 🤖

🚀 Federated Learning as Locally Weighted Learning? Let’s Dive In! 🤖 In this video, we explore Federated Learning through the lens of Locally Weighted Learning (LWL). Instead of treating FL as a standard optimization problem, we frame it as a form of adaptive, locally weighted model updating, where devices assign different importance to local data points when refining global models. 🔍 Key Concepts Covered: ✅ Federated Learning as a weighted learning process ✅ How local models adapt based on data distribution ✅ The role of weighting schemes in decentralized learning 💡 Why This Matters: Understanding Federated Learning as a locally weighted learning method helps explain how personalized models emerge while preserving privacy and reducing communication costs. 📢 Do you think this is a useful perspective? Let me know in the comments! 📚 More Learning Resources: 👉 https://FederatedLearningAalto.github.io 🔔 Subscribe for More AI & ML Insights! #FederatedLearning #MachineLearning #AI #LocallyWeightedLearning #PersonalizedML #DeepLearning