williambdean/pymc-mlflow-example
MLflow logging for PyMC
This project helps data scientists and machine learning engineers easily track and manage their PyMC Bayesian modeling experiments. You input your PyMC model code, and it automatically logs key parameters, performance metrics, and any relevant files (like model plots) into MLflow. This makes it simpler to compare different model versions and understand their performance over time.
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Use this if you are building Bayesian models with PyMC and need a structured way to log and compare your experiment results using MLflow.
Not ideal if you are not using PyMC for your modeling or are not already using MLflow for experiment tracking.
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Aug 31, 2025
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