In This session we talked about the earlier model we made in chapter 3 for churn prediction.
This chapter containes the deployment of the model. If we want to use the model to predict new values without running the code, There's a way to do this. The way to use the model in different machines without running the code, is to deploy the model in a server (run the code and make the model). After deploying the code in a machine used as server we can make some endpoints (using api's) to connect from another machine to the server and predict values.
To deploy the model in a server there are some steps:
- After training the model save it, to use it for making predictions in future (session 02-pickle).
- Make the API endpoints in order to request predictions. (session 03-flask-intro and 04-flask-deployment)
- Some other server deployment options (sessions 5 to 9)
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