Disclaimers:

This post is more geared to people who want to expose a machine learning model as part of a data science portfolio than for people seeking to deploy to a production grade.

This post also makes use of AWS services which may be chargeable depending on your situation. Be sure to take precautionary measures such as creating a budget to avoid unpleasant surprises.

More and more now the presentation of a portfolio has become important as part of the search for a position especially when it is the first one. Nowadays in data science, it has become important not only to master the basics of machine learning but also to know how to deploy models.

In this post, it will be about deploying a scikit-learn machine learning model using serverless services because it allows us to let the model deploy and only pay for the time it will be used unlike using a server.

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