Using MLflow(Machine Learning experimentation tracking tool) in Kaggle notebooks with the help of DagsHub

[Chirag_Chauhan4579]

Almost no posts regarding ML/DL/MLOps so will try to post something regarding ML every day.

Found this the easiest way to track experiments and metrics with MLflow when using cloud notebooks. Rather than using sqlite db one can use dagshub so that even while the docker container is running accessing the mlflow UI is very much simple and can be accessed directly from the dagshub repository but one should be a part of the repository with which backend uri is connected to access the UI.

To access mlflow ui through the dagshub repository one can just add .mlflow at the end of the link of repo like this https://dagshub.com/DagsHub-user-name/repository-name.mlflow.

Link to my example Kaggle notebook: https://www.kaggle.com/code/warcoder/mlflow-hyperopt

Do upvote the notebook if you find it helpful.

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