> Everyone wants to do machine learning, but nobody seems to want to learn statistics.
i think there are are a fair amount of people who want to learn the stats .. even some who want to learn the analysis.
it appears that some things that can be phrased in terms of iterative numerical computation can be difficult because there are probably some properties of the limiting behavior of those computations that can't be learned because they've yet to be discovered.
nonetheless, i (maybe?) get what the parent post is generally saying -- as someone who knows nothing about tensorflow, i wonder if tensorflow users are generally interested in flatness, etc., which (exact sequences of tensor products) is the only guess that i've made about what a portmanteau of "tensor" and "flow" uses as a conceptual model.
i wonder if the difficulty of 'machine learning' is that people tend to approach it as its own thing with its own special, entirely separate bag of tricks. certainly there will be some tricks unique to these iterative statistical techinques.
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however, i don't think the original article gives enough due-deference to the actual workaday difficulties, challenges, and [non-monetary] rewards of software development in industry: if ML, ANNs, etc. are, as some say, essentially "computer psychology," then being productive on with a team of developers to ship a business product is peddle-to-metal human psychology..
i think there are are a fair amount of people who want to learn the stats .. even some who want to learn the analysis.
it appears that some things that can be phrased in terms of iterative numerical computation can be difficult because there are probably some properties of the limiting behavior of those computations that can't be learned because they've yet to be discovered.
nonetheless, i (maybe?) get what the parent post is generally saying -- as someone who knows nothing about tensorflow, i wonder if tensorflow users are generally interested in flatness, etc., which (exact sequences of tensor products) is the only guess that i've made about what a portmanteau of "tensor" and "flow" uses as a conceptual model.
i wonder if the difficulty of 'machine learning' is that people tend to approach it as its own thing with its own special, entirely separate bag of tricks. certainly there will be some tricks unique to these iterative statistical techinques.
----
however, i don't think the original article gives enough due-deference to the actual workaday difficulties, challenges, and [non-monetary] rewards of software development in industry: if ML, ANNs, etc. are, as some say, essentially "computer psychology," then being productive on with a team of developers to ship a business product is peddle-to-metal human psychology..