Supporting Arbitrary ML Models with MlFlow (Using PyCaret as an Example)

Benjamin Tan Wei Hao
DKatalis
Published in
3 min readMar 14, 2022

--

MlFlow model tackling various tasks.

MlFlow is awesome. We use it all the time to track our ML models and their artifacts. Logging model training runs are super easy, and if you need any custom logic, the API is also pretty easy to use.

The one small caveat to this is that the model should already be supported by MlFlow. See the following list for all the models that MlFlow…

--

--

Benjamin Tan Wei Hao
DKatalis

Author of The Little Elixir & OTP Guidebook, Mastering Ruby Closures, Building an ML Pipeline in Kubeflow. | Currently: Product Owner at @dkatalis.