So, this week on ML Zoomcamp, we're to learn how to deploy a machine learning Model.
Previously in the Zoomcamp, I've had issues concentrating when watching the video lectures. I generally do not "enjoy" video tutorials that much. So this time, I decided to read the notes on the repository and it was a breeze.
A much better experience. Maybe I should have been doing this all this while. I guess this is why the idiom is "Read the Docs" as opposed to "Watch the tutorial".
Anyways, so back to deployment. Generally ML Models are usually built on Notebooks. Or at least, that's how they've been built so far in the course. But you can't deploy a notebook for other users to connect to, as far as I know. You have to create a public API and host it on a platform like AWS.
But first, we have to export the model from the Notebook. Which we used Pickle for, and it outputted a binary file.
