What most commonly determines the success of an applied data science project?
- A Framing the right question and having reliable data, more than the modelling technique
- B The sophistication of the algorithm
- C The size of the compute cluster
- D The number of features engineered
Answer
Framing the right question and having reliable data, more than the modelling technique
Most production failures are methodology and data problems rather than modelling problems, which is why the framing stage matters most.
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