"The difficulty is that machine learning is a fundamentally hard debugging problem. Debugging for machine learning happens in two cases: 1) your algorithm doesn't work or 2) your algorithm doesn't work well enough."
Read it!An explanation with examples illustrating the motivation to use SQL for fetching data from a database instead of directly loading the data into Pandas.
Read it!A five-step method for transitioning from problem to data-backed decision making.
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