[D]How to "productionize" a jupyter notebook in a technical interview?

Hi redditors!

I've been tasked with an technical homework that asks me to "productionize" a Jupyter notebook. The notebook's workflow is as follows:

1. Reads data from a CSV.
2. Pre-processes the data.
3. Trains a machine learning model.
4. Makes predictions.

My initial thoughts are:

1. **Separation of Concerns**: Break the notebook down into distinct components - data processing, model training, and inference.
2. **Containerization**: Write a Dockerfile to ensure the environment is reproducible and isolated.
3. **API for …

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