| > implies that they're thoroughly disconnected from the realities of ML devops on the cloud FWIW, I deal with "the realities of ML devops on the cloud" nearly every day -- both at work and in hobby projects. The comments here make me think I failed to get my main intent across in the post. I actually agree with many of the concrete claims you make here, but they have little to do with the arguments I saw myself as making. The miscommunication was apparently so complete that if I tried to dig into specific points you make here, I'd end up effectively re-writing my post all over again. It was kind of exhausting to write the first time, so I'd prefer not to. That said, as an example of something I didn't mean to say: I definitely don't think the sklearn API ought to be standard across ML, certainly not the pickling part! It is a well-designed API that's just right for its own limited context, and ought to inspire others to develop other APIs that are similarly well-designed for their contexts. I only added the comment about Keras and pickle because I had quoted a tweet that literally said Keras was sklearn API compatible, and felt sort of obligated to point out that this was strictly false. Insofar as this relates to the larger point at all, it does so only as evidence that people like Chollet don't have a deep understanding of the thing they say they're inspired by. |