bodywork-pipeline-with-aporia-monitoring
bodywork-pymc3-project
| bodywork-pipeline-with-aporia-monitoring | bodywork-pymc3-project | |
|---|---|---|
| 1 | 1 | |
| 4 | 13 | |
| - | - | |
| 0.0 | 5.3 | |
| almost 2 years ago | almost 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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bodywork-pipeline-with-aporia-monitoring
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Calling Aporia from Bodywork Pipelines to Monitor Models in Production
Monitoring models for drift and degradation is not easy - theoretically or practically. In this example project we show to outsource these problems to Aporia’s model monitoring platform, by using their Python client from within a Bodywork pipeline.
bodywork-pymc3-project
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A tutorial on how to handle prediction uncertainty in production systems, by using Bayesian inference and probabilistic programs
All of the code is hosted in a GitHub repo, that you can use as a template for your own projects.
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