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Friendly federated learning 🌼
Practical AI: Machine Learning, Data Science, LLM
Use Cases and Data Confidentiality Challenges in Federated Learning
There is a difference between centralized learning and federated learning, especially in terms of convergence time and the impact of averaging process./nComparisons between centralized and federated learning are somewhat artificial, as federated learning is often the only option in reality./nBy making deep learning models bigger, better accuracy and other performance metrics can be achieved./nRecent advances in deep learning and machine learning are often fascinating and often in the context of webscale companies.
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