Description
Product Category: Step-by-Step Guides
Format: PowerPoint
A Step-by-Step Guide to Federated Learning for Decentralized AI Models
Federated learning (FL) is a transformative approach to machine learning that enables the training of models across decentralized devices without sharing sensitive data. By ensuring data remains local, this technique addresses privacy concerns while leveraging distributed datasets to improve model accuracy and generalizability. Federated learning is particularly beneficial for industries handling sensitive information, such as healthcare, finance, and IoT. Here is a structured approach to implementing federated learning for decentralized AI models.
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