This topic describes how to create experiments and deploy experiment models by using the heart disease prediction template.

Prerequisites

  • Machine Learning Platform for AI is activated. For more information, see Purchase.
  • A project is created. For more information, see Create a project.

Procedure

  1. Go to a Machine Learning Studio project.
    1. Log on to the PAI console.
    2. In the left-side navigation pane, choose Model Training > Studio-Modeling Visualization.
    3. In the upper-left corner of the page, select the region that you want.
    4. Optional:In the search box on the PAI Visualization Modeling page, enter the name of a project to search for the project.
    5. Find the project that you want and click Machine Learning in the Operation column.
  2. Create and run an experiment.
    1. In the left-side navigation pane, click Home.
    2. In the Templates section, click Create below Heart Disease Prediction.
    3. In the New Experiment dialog box, set the Name parameter and use the default values for other parameters.
    4. Click OK. Wait about 10 seconds for the canvas of the experiment to appear. The following figure shows the canvas.Experiment of heart disease prediction
    5. In the upper part of the canvas, click Run. When the experiment is running, you can right-click the components to view their output information.
  3. Deploy the model.
    1. After the experiment stops running, move the pointer over Deploy and select Online Model Service.
    2. Click Next.
    3. In the Resources And Models panel, set the Custom Model Name parameter and use the default values for other parameters.
    4. Click Deploy.
    5. When the status of the model changes from Creating to Running in the State column, the model is deployed.
      Note When you do not use the model, click Stop in the Operating column. This saves costs.