ruyakubu / azure-ml-notebook-diabetes-training

Learn how to connect to Azure Machine Learning workspace and create an experiment

azure-ml-notebook-diabetes-training

In this tutorial, you will create an experiment that connects to Azure Machine Learning workspace; train a simple scikit-learn model based on the diabetes data set, register the model; deploy the model to an Azure Container Instance; and test the trained model. After completing this tutorial, you will have the practical knowledge of the SDK to scale up to developing more-complex experiments and workflows.

In this tutorial, you learn the following tasks:

• Connect your workspace and create an experiment
• Load data and train a scikit-learn model
• View training results in the portal
• Retrieve the best model
• Register the model to your workspace
• Create the scoring script for your web service
• Create environment file for a Docker image
• Deploy the model to ACI
• Test the deployed model using the HTTP web service end point

To run on a Cloud-based Nookbook VM

Here are the following steps you need to take:

1. Clone this github repository
2. Create an Azure Machine Learning service workspace
3. Create a cloud notebook server in your workspace.
   1. Sign in to Azure Machine Learning studio.
   2. Select your subscription and the workspace you created.
   3. Once on the ML studio page, select Compute on the left.
   4. Select +New to create a notebook VM.
   5. Provide a name and select configuration for your VM. Then click Create.
   6. Wait until the status changes to Running 4 Select Notebooks on the left.
4. On the Notebooks page, click on the Upload files (the up arrow) icon to upload the demo-diabetes-experiment-sdk-train.ipynb file from the github repository
5. Execute the Jupyter notebook script by either clicking on the Run link on the run Notebook server page, or Click on the [...] link to open in Jupyter and run the script.