
Why Are Machine Learning Projects So Hard to Manage? - pplonski86
https://medium.com/@l2k/why-are-machine-learning-projects-so-hard-to-manage-8e9b9cf49641
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pplonski86
There are so many things that can go wrong in machine learning project. For
example:

\- the core of any ML project is an input data pipeline (the input ETL). There
can be some row missing in one table and the whole solution will break

\- the ML models are computing predictions on new data - we can only assume
that they will work as expected, but the true is that no-one knows how they
will behave

\- the ML models often tend to be very complex = hard to understand = hard to
debug (there are some explainers for ML/AI, but it is one more complex module
in the project :))

I agree 100% with article's author that you should start with something super-
simple that works, and then try to iterate, one thing at a time

