https://github.com/markdouthwaite/serverless-scikit-learn-demo

A repository providing demo code for deploying a lightweight Scikit-Learn based ML pipeline modelling heart disease data as a Google Cloud Function.
https://github.com/markdouthwaite/serverless-scikit-learn-demo

data-science google-cloud google-cloud-function machine-learning machine-learning-api machine-learning-projects scikit-learn serverless tutorial

Last synced: about 2 months ago
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A repository providing demo code for deploying a lightweight Scikit-Learn based ML pipeline modelling heart disease data as a Google Cloud Function.

• Host: GitHub
• URL: https://github.com/markdouthwaite/serverless-scikit-learn-demo
• Owner: markdouthwaite
• License: mit
• Created: 2020-07-22T20:32:09.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2022-09-30T18:59:48.000Z (over 2 years ago)
• Last Synced: 2023-03-05T12:50:21.054Z (almost 2 years ago)
• Topics: data-science, google-cloud, google-cloud-function, machine-learning, machine-learning-api, machine-learning-projects, scikit-learn, serverless, tutorial
• Language: Python
• Homepage:
• Size: 29.3 KB
• Stars: 9
• Watchers: 1
• Forks: 18
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# serverless-scikit-learn-demo

A repository providing a suggested project structure and simple design pattern for 

deploying lightweight Scikit-Learn Pipelines as Google Cloud Functions. The example

code provided fits a simple Logistic Regression model to predict whether a given 

patient has heart disease or not. This dataset is [taken from Kaggle](https://www.kaggle.com/ronitf/heart-disease-uci).