3 ms·
Not the OP but: * Problem definition * Infrastructure * Data transformation * Exploratory analysis (arguably part of model work) * Results presentation Th
by mshron 14y ago
Not the OP but:
* Problem definition
* Infrastructure
* Data transformation
* Exploratory analysis (arguably part of model work)
* Results presentation
Then again, this is an ongoing disagreement I have with the Kaggle folks over what constitutes "data science," where I'm pretty confident that "applied machine learning" is a better explanation of what their contests are about.
- rm999 14y agoI kind of got them to say it here: https://news.ycombinator.com/item?id=4655927 https://news.ycombinator.com/item?id=4655927 BTW, I'm a big fan of the data analysis that came out of okcupid, is that all your work?
- lrei 14y agoI see. Thanks. I'd say data transformation is a part of feature engineering (commonly the bulk of the effort in a ML application). And exploratory analysis is part of model work. W/o those 2 one would be building a model out of dreams and wishes. Data Science is probably a poorly chosen description. I'd say common use includes infrastructure work which for most of us consists in engineering work.