In the majority of cases, not much. My point is more that many people who claim expertise in machine learning do not have a holistic understanding of the field; their knowledge is patchy and they aren’t able to implement a solution to more than the most general of problems. It would be like a car mechanic that can change the oil but doesn’t know how to locate and fix a leak.
Most neural networks that perform well nowadays are highly specialized to a particular problem domain, and I gave an example of an approach that might be used by someone designing a neural network that is invariant to certain types of symmetries on the input data. This isn’t something a typical DS/ML bootcamper would know how to handle, or even how to approach, despite their claims of expertise.
Most neural networks that perform well nowadays are highly specialized to a particular problem domain, and I gave an example of an approach that might be used by someone designing a neural network that is invariant to certain types of symmetries on the input data. This isn’t something a typical DS/ML bootcamper would know how to handle, or even how to approach, despite their claims of expertise.