Focus on gathering signals rather than nitpicking on small details. Before rejecting a candidate for a small detail, ask yourself if that issue could be easily addressed in a code review or mentoring session. If so, how important is that detail really?
In my opinion, MOOCs that taught ML often give people the false impression that anyone can be a ML practitioner. To the naive, ML is simply a few lines of code that involves .fit() and .predict(), and that is because MOOCs represent it in such a way that one can get started with ML with relative…
…eep neural net models, and other more complex features like transformers and bi-directional coding. Understan…eep neural net models, and other more complex features like transformers and bi-directional coding. Understanding why some state-of-the-art models work better than others is important as well, alongside concepts like transfer learning and meta learning.
…te most of them (only the ones in bold). I was stuck in what I call a MOOC self perpetuating cycle. The ease of access to knowledge made it natural to go from one course to the next, often not completing the prior course due to the brevity of the topics covered which made my interest fleeting.