Machine Learning Bookcamp

5 Deploying machine learning models

This chapter covers

• Saving models with Pickle
• Serving models with Flask
• Managing dependencies with Pipenv
• Making the service self-contained with Docker
• Deploying it to the cloud using AWS Elastic Beanstalk

As we continue to work with machine learning techniques, we’ll keep using the project we already started: churn prediction. In chapter 3, we used Scikit-learn to build a model for identifying churning customers. After that, in chapter 4, we evaluated the quality of this model and selected the best parameter C using cross-validation.

We already have a model that lives in our Jupyter Notebook. Now we need to put this model into production, so other services can use the model to make decisions based on the ...