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They teach it on their personal data, then summarize and encrypt the product’s new configuration. The model updates are sent again to the cloud, decrypted, averaged, and integrated into the centralized model. Iteration following iteration, the collaborative schooling continues until eventually the product is completely trained. Enterprise adoption of ML https://website-uae05059.thenerdsblog.com/40582932/5-simple-statements-about-data-engineering-services-explained

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