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It’s fine when the library is a tight abstraction. Unfortunately, ML libraries are leaky. Example: take a classification model and change the output dimensions
by mirker 4y ago
It’s fine when the library is a tight abstraction. Unfortunately, ML libraries are leaky.
Example: take a classification model and change the output dimensions without understanding the model.
- nmstoker 4y agoYes, the challenge people then face is that if they lack too much intuition for the subject, they can't spot obvious issues. We've all seen how ML people don't necessarily have to have the skills to solve a problem (ie i don't need to speak Vietnamese to make a "passable" ML translator) but it's not long before the lack of knowledge starts to show up embarrassing shortfalls - being too arms length about any topic is a recipe for disaster!