Great writeup. I do wonder about the "ability to do harm" in machine learning without understanding fundamentals. I just heard a talk from a data scientist this Monday who built a model that includes zip code to predict mortality risk, and I asked about "how did you control for disparate impact" to no answer (compliance signed off on the model...that's not an answer).
Going the other way, like you say, to be an expert the fundamentals are key. Maybe you don't need to _start_ there, but the goal should be to get there, for the reasons that I think Julia Evans (https://jvns.ca/about/) sums up well (emphasis mine):
> I have one main opinion about programming, which is that deeply understanding the underlying systems you use (the browser, the kernel, the operating system, the network layers, your database, HTTP, whatever you’re running on top of) is essential if you want to do **technically innovative work and be able to solve hard problems**.
Great writeup. I do wonder about the "ability to do harm" in machine learning without understanding fundamentals. I just heard a talk from a data scientist this Monday who built a model that includes zip code to predict mortality risk, and I asked about "how did you control for disparate impact" to no answer (compliance signed off on the model...that's not an answer).
Going the other way, like you say, to be an expert the fundamentals are key. Maybe you don't need to _start_ there, but the goal should be to get there, for the reasons that I think Julia Evans (https://jvns.ca/about/) sums up well (emphasis mine):
> I have one main opinion about programming, which is that deeply understanding the underlying systems you use (the browser, the kernel, the operating system, the network layers, your database, HTTP, whatever you’re running on top of) is essential if you want to do **technically innovative work and be able to solve hard problems**.