Older article will guide you through how to use scikit-learn, pickle, Flask, Microsoft Azure and ipywidgets to fully deploy a Python machine learning algorithm into a live, production environment. By Graham Harrison.
You will get these steps describing how machine learning algorithm could be fully deployed into a live production environment so that it could be “consumed” in a platform-agnostic way:
- Develop a machine learning algorithm
- Make an individual prediction from the trained model
- Develop a web service wrapper
- Deploy the web service to microsoft Azure
- Add the Azure app service extension to VS Code
- Building a client application to consume the Azure deployed web service
There are quite a few steps involved, but using readily available libraries and free tools including scikit-learn, pickle, flask, Microsoft Azure and ipywidgets we have constructed a fully working, publicly available cloud deployment of a machine learning algorithm and a fully functioning client to call and consume the web service and display the results. Nice one!
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