Source: thenewstack.io
Refresh Your Stale Machine Learning Models with DVC
https://twitter.com/flippedcoding What happens when the https://thenewstack.io/category/machine-learning/ model you’ve worked so hard to get to production becomes stale? You usually have to figure out where the data drift started so you can determine what input data has changed.
We’ll be working with a project from https://evidentlyai.com/blog/tutorial-1-model-analytics-in-production that demonstrates what it would be like to work with a production model that experiences data drift over time.
When the data in production starts to look different from the data that your model was trained on, this is called data drift.
This is one of the processes you can use to keep your production models from going stale.
We’ll be working with a project from https://evidentlyai.com/blog/tutorial-1-model-analytics-in-production that demonstrates what it would be like to work with a production model that experiences data drift over time.
When the data in production starts to look different from the data that your model was trained on, this is called data drift.
This is one of the processes you can use to keep your production models from going stale.
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