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Machine learning model serve as API in production with swagger documentation. #Block5

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MKrouma/Jedha_ML_PROD

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ML Production

Project to deploy a trained model to production via an API. That's the last project of Deployment module at Jedha Bootcamp.

Description

The purpose of this project is to deploy an ML model that predicts white wine quality using some inputs parameters. We have as input data/winequality.csv et model/model.joblib.

Workflow

To go on this project, we follow this workflow :

Create project folder
Init git repository
Create virtual environnments
Retrained model (optional)
Create flask api endpoint to predict
Write documentation (flask restx)
Deploy on heroku
Set CI Github-Heroku

Tools

Flask
Flask restx
Git & Github
Heroku

Results

API in production : https://jedhamlproduction.herokuapp.com/

Authors :

Mamadou Krouma
MKrouma

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Machine learning model serve as API in production with swagger documentation. #Block5

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