🐾Top 5 tips for productionising your ML code🐾

1️⃣ Don’t create complex data processing scripts in Jupyter notebooks, they should be used for EDA and visualisations.

2️⃣ Variables and functions names should be easy to understand for others and consistent across the script.

3️⃣ Use docstrings to add documentation, making it easier to understand and change the code.

4️⃣ Don’t write one monolithic script, split it into steps, making it easier to debug and maintain your code.

5️⃣ Don’t create custom functions until you explore native Python functions for the same functionality. Many native libraries are written in C (numpy, scipy), so they are faster than ones written by you.

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