This diagram highlights the importance of Machine Learning Engineering for Data/AI projects and the community. And it doesn’t even show one of my favorite topics: software design patterns, an outrageously important subject that helps with code maintainership, extensibility, standards, organization, beauty, which in turns help with (much) higher productivity of Data professionals.
![Technical components around the machine learning code required to make a mature AI product](https://avi.alkalay.net/articlefiles/2023/06/ml-engineering-1024x382.png)
Diagram extracted from Hidden Technical Debt in Machine Learning Systems, by Google reaserchers, which also says that “a mature system might end up being (at most) 5% machine learning code and (at least) 95% glue code”.
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