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Parallel issue: people who fit complex models when simple descriptive statistics would be more useful/a better fit.
by gbrown 7y ago
Parallel issue: people who fit complex models when simple descriptive statistics would be more useful/a better fit.
- mlthoughts2018 7y agoThis is a byproduct of hiring bootcamp grads or tasking a modeling project to engineers who read some tutorials. People think they can scan a few Jupyter notebooks and then professionally solve statistics problems. People wonder why it’s hard and expensive to hire ML engineers... because they actually solve these problems with craft. Meaning, they systematically grow understanding of the data, start with simple models, and have well articulated reasons explaining cases when complexity is justified.
- ma2rten 7y agoIt's the machine learning version of people who use hadoop if they could have used command-line utilities.