Instructions
For this request, you are to create a predictive model in Azure ML Studio for the attached dataset and turn in a report as specified in the following pages. You should use whichever data preparation, modeling, and model assessment techniques that were covered in this portion of the class that you believe result in the best model.
You will be performing an Exploratory Data Analysis, Model Development and Training, and Model Deployment activities and preparing a report in PowerPoint form.
See the sample report that is part of this request for a template and example.
When you are complete, save this file as a PDF and upload it to Gradescope.
As a reminder, the work that you submit must be done individually. Unlike the request requests, working together is not permitted and the graders will be looking for identical solutions.
For this request, you will use Azure ML Studio Designer to build a classification model to predict the likelihood of a patient developing Chronic Heart Disease (CHD) in the coming ten years. The dataset you will be using has been distributed with this exam and consists of the variables on the following page.
Note On Model Deployment
When complete, create a real-time endpoint for your model and copy the REST Endpoint URL and the authentication key into a Google drive spreadsheet that will be published.
The TAs will run scripts to independently evaluate your model performance sometime.
Once complete, a message will be posted on Piazza and you should then delete your endpoint.
Final Report Structure
Please follow the provided template/example and structure your final report into the following three sections:
Exploratory Data Analysis
Model Development
Model Deployment
Final Report Outline/Grading Rubric
Report contents
Attribute summary
Data cleansing - summary of decisions made
Data cleansing pipeline (portion of your overall pipeline)
Univariate analysis
Bivariate analysis (each variable vs the response variable)
Feature section/engineering decisions
Model pipeline screenshot
Model evaluation results screenshot
Inference pipeline screenshot
REST Endpoint URL and authentication key (in PPT and in Google drive spreadsheet)
Screenshot of scored test dataset
Model performance
Based on TAs calling your endpoint with test dat