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This is a recipe to get very good at basic analysis. It won't prepare you for the day-to-day responsibilities of a data scientist, though.
by achompas 13y ago
This is a recipe to get very good at basic analysis. It won't prepare you for the day-to-day responsibilities of a data scientist, though.
- xiaoma 13y agoWhat do you feel would needed to be added to the mix in order to prepare a person for the day-to-day responsibilities of a data scientist? Also which of those responsibilities do you see as most challenging?
- achompas 13y agoYeah, sorry for the snarky one-liners. I wrote a bit more here: https://news.ycombinator.com/item?id=6060821 https://news.ycombinator.com/item?id=6060821 There are two pieces Kaggle can't help you with: working through the full research cycle and developing performant models. It also emphasizes the wrong goals (for example error minimization is almost never your primary goal), but I need to work at some point and have spent enough time in this thread, so I'll skip that. :P Email me if you want to discuss, though. Anyway Kaggle can't help with the full research cycle, since you're not identifying a relevant question yourself (this is surprisingly hard) or presenting your answer to others. The latter is hard for any route, since you really only encounter that type of volume in industry.