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Bleeding edge is great for fun and personal development, Jeremy (with the fast.ai team as a whole) is wonderful and all that, but you need to have your own suitable case study to make the most of such techniques and implementation... nlp for the time being, it was image processing when they were just starting and I followed their courses. In 2020 or year V, VI or VII of this new machine learning explosion, generalists cannot not do much on their own anymore imho.





My impression from 3 years of working under the job title of "data scientist" is that generalists have a huge advantage compared to specialists. Data scientists these days have to have some idea of how each step in the data science workflow works, including non-technical aspects like business, office and institutional politics, and domain knowledge.



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