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Labs

Creating a Classification Model with Azure ML Designer

In this hands-on lab, you are working as a data scientist for AIDoctor, a medical clinic. You’ve been asked to come up with a model that can be used to predict if a patient is diabetic, based on factors such as age, blood pressure, BMI, and more. You’ll use Azure Machine Learning studio and Azure Machine Learning designer to create a classification model that will predict if a patient is diabetic or not. You’ll also get to create an inference pipeline during this lab.

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Labs

Path Info

Level
Clock icon Beginner
Duration
Clock icon 1h 0m
Published
Clock icon Dec 16, 2021

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Table of Contents

  1. Challenge

    Open the Azure ML Studio and Create a New Dataset

    In the Azure ML studio, create a new dataset using the diabetes data file from Microsoft.

  2. Challenge

    Review the Dataset

    Take a look at the data you’re working with and see if there are any missing values or values that will cause issues.

  3. Challenge

    Design a Pipeline to Predict If Patients Have Diabetes and Review Evaluation Results

    Drag and drop modules to create a pipeline that will train a classification model. After it runs, review the evaluation results and metrics.

  4. Challenge

    Create and Run an Inference Pipeline

    Create a real-time inference pipeline by adding the Web Service Input module to the pipeline and moving its output to the Apply Transformation module. Then, remove the Evaluate Model module. After making those modifications, run the pipeline.

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