This is doubly true in Machine Learning Engineering. Knowing what methods to avoid is just as important to know what might work well and why. Importantly a bunc

This is doubly true in Machine Learning Engineering. Knowing what methods to avoid is just as important to know what might work well and why. Importantly a bunch of Data Science techniques — and I use data science in the sense of making critical team/org decisions — is also as important for which you should understand a bit of statistics not only data driven ML.