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kipkc09's avatar
kipkc09
New Member
1 year ago
Solved

How to log/register ML model with MLFlow, with the model items in specified folder in workspace

Hi, I'm trying to use MLFlow in Fabric notebook. I have logged the trained model using: mlflow.sklearn.log_model(model1, artifact_path="model_path", signature=signature). I have found that model1 ...
data science
experiment
ml model
notebook
  • v-pnaroju-msft's avatar
    v-pnaroju-msft
    1 year ago

    Thankyou, nilendraFabric, for your response.

    Hi kipkc09,

    We appreciate your inquiry through the Microsoft Fabric Community Forum.

    In addition to the response provided by nilendraFabric , and to facilitate better workspace organization across projects, please find below some approaches that may help resolve the issue:

    1. Prefix model names with project identifiers during registration.

      mlflow.register_model(model_uri, "ProjectA_Model_v1")

    2. Use MLflow tags to organize and filter models.

      mlflow.set_tags({
      "project": "ProjectA",
      "team": "Analytics",
      "version": "v1.0"
      })

    3. Create and log runs to separate experiments per project.

      mlflow.set_experiment("/ProjectA/ML_Experiments")

    If you find our response helpful, kindly mark it as the accepted solution and provide kudos. This will assist other community members facing similar queries.

    Thank you.




v-pnaroju-msft's avatar
v-pnaroju-msft
Icon for Community Support rankCommunity Support
1 year ago

Thankyou, nilendraFabric, for your response.

Hi kipkc09,

We appreciate your inquiry through the Microsoft Fabric Community Forum.

In addition to the response provided by nilendraFabric , and to facilitate better workspace organization across projects, please find below some approaches that may help resolve the issue:

  1. Prefix model names with project identifiers during registration.

    mlflow.register_model(model_uri, "ProjectA_Model_v1")

  2. Use MLflow tags to organize and filter models.

    mlflow.set_tags({
    "project": "ProjectA",
    "team": "Analytics",
    "version": "v1.0"
    })

  3. Create and log runs to separate experiments per project.

    mlflow.set_experiment("/ProjectA/ML_Experiments")

If you find our response helpful, kindly mark it as the accepted solution and provide kudos. This will assist other community members facing similar queries.

Thank you.




spark21wood's avatar
spark21wood
Icon for Microsoft Employee rankMicrosoft Employee
10 months ago

All of my MLFlow experiments show in the root directory of the Workspace in Fabric.  How do I set the path location to be a subfolder in the Fabric workspace?

  • v-pnaroju-msft's avatar
    v-pnaroju-msft
    Icon for Community Support rankCommunity Support
    10 months ago

    Hi spark21wood,

    Based on my understanding, MLflow experiments in Microsoft Fabric currently appear only at the workspace root, and there is no built‑in mechanism to assign them to a subfolder at creation.
    Please consider the following workaround approaches which may help resolve the issue:
    1. Simulate folders in the workspace UI:
    mlflow.set_experiment("/ProjectA/ML_Experiments/Experiment1")
    2. Specify a Lakehouse or external storage path when creating the experiment to store artifacts in a structured folder:
    mlflow.create_experiment(
    name="/ProjectA/ML_Experiments/Experiment1",
    artifact_location="abfss://<container>@<storage-account>.dfs.core.windows.net/ProjectA/ML_Experiments/Experiment1"
    )
    mlflow.set_experiment("/ProjectA/ML_Experiments/Experiment1")

    We hope that the information provided will help resolve the issue. Should you have any further queries, please feel free to contact the Microsoft Fabric community.
    Thank you.