Deployment of a machine learning model is an important phase in the data life cycle. Such a model could be a minimum viable product (MVP) that would allow relevant stakeholders access to the model from which to test and experiment with, which could lead to valuable feedback for further model improvement.
Model deployment may seem like a difficult and daunting task but it does not have to be. In this article, you will learn how to easily deploy a machine learning app to the cloud using Heroku. The advantage of deploying to Heroku is that we don’t have to worry about anything related to the underlying operating system (i.e. no more installing updates, dependencies or maintenance) on which the app is running on.
It should be noted that this article has an accompanying video (How to Deploy Data Science Web App to Heroku) that can serve as a supplement or visual aid from which to refer to.
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