deep-diver/Continuous-Adaptation-for-Machine-Learning-System-to-Data-Changes
https://blog.tensorflow.org/2021/12/continuous-adaptation-for-machine.html
This project helps MLOps engineers ensure their machine learning models stay accurate even when the real-world data they encounter changes over time. It takes in continuously updated data and an existing machine learning model, then automatically retrains and redeploys the model to adapt to new data patterns. This is for MLOps engineers responsible for maintaining the performance and reliability of deployed ML systems.
No commits in the last 6 months.
Use this if you need a robust system to automatically detect and adapt your machine learning models to data drift or concept drift in production.
Not ideal if you are looking for a simple model training script or are unfamiliar with MLOps concepts like pipelines, data drift, and cloud infrastructure.
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Apache-2.0
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Last pushed
Dec 10, 2021
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