It really is hard to separate ML & statistics - any competent practicioner of ML appreciates the statistical achievements that made Machine Learning methods possible. And statisticians must understand that to help automate decision-making systems, using learning methods/boosting is a viable option.
The debate around nomenclature (ML/stats/AI) seems limited to the academic community. Most data scientists I've met tend to accumulate a repertoire of tools from different fields, rather that side with either Machine Learning or Statistical communities.
It really is hard to separate ML & statistics - any competent practicioner of ML appreciates the statistical achievements that made Machine Learning methods possible. And statisticians must understand that to help automate decision-making systems, using learning methods/boosting is a viable option.
The debate around nomenclature (ML/stats/AI) seems limited to the academic community. Most data scientists I've met tend to accumulate a repertoire of tools from different fields, rather that side with either Machine Learning or Statistical communities.