Ask HN: Where is AI/ML actually adding value at your company?

Re:Ask HN: Where is AI/ML actually adding value at your comp... by shmageggy on Monday December 12, 2016 @09:29PM (#13163987)

If I'm reading this correctly, it's just wrong. Whatever the distinction between data analysis and ML might be, it is more than just whether your data and predicted quantities are discrete or continuous.

> Categorical Independent vs. Categorical Dependent, for example, is fairly restrictive, as makes logical sense. You may cross-tabulate, you may score likelihood based on previous observation, but obviously, because all of the data involved are non-numeric, there's no chance for regression, ANOVA, etc

If you are implying that categorical -> categorical predictions are not ML: as a counter example, natural language is a categorical (words) input that could be used to predict any number of categorical variables (parse trees, semantic categories, etc). I think it's safe to say that the field of NLP is doing machine learning.

[ Parent | on HN ]

Re:Ask HN: Where is AI/ML actually adding value at your comp... by Bartweiss on Tuesday December 13, 2016 @12:56PM (#13168847)

Thanks for the sanity check. I read that reply, and got bogged down enough that I was worried my initial reaction of "what, that's not relevant!" was born of ignorance. Discrete/continuous is a distinction worth making, but as a hidden 'definition' for ML I really don't understand it.

[ Parent | on HN ]