Is having a background in nonparametric estimation a useful path into machine learning anymore? [D]

I’m a Masters student in Statistics. My background is pretty much all grounded in foundational statistical theory, and my thesis is on nonparametric estimation (nonparametric regression, specifically). Basically my “machine learning” knowledge stems from some classical nonparametric estimation books like (Tysbakov, Wasserman, Tibshirani/Hastie, and Friedman). The elements of statistical learning is pretty much the background I have in machine learning as my thesis is concerning the intersection between classical methods for nonparamrtric regression like tree based methods, kernel smoothers and …

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