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What doesn’t help is that these techniques are increasingly taught in undergrad programs and short term data science experiences. More content, more tools, no
by avs733 6y ago
What doesn’t help is that these techniques are increasingly taught in undergrad programs and short term data science experiences.
More content, more tools, no time for understanding of the full scope of analysis.
Statistical education has called for the use of real data for a long time and it is still woefully absent in undergrad statistics and probability courses. Students are given clean/cleanish data so they can be evaluated on the correct application of tools, not on a full stack process of data sense making. When I took over our stats course I took out the coding (instructors were arguing over R vs Matlab) and put in excel. Excel opens their eyes because it can’t make math invisible like R can...they can’t obfuscate their mistakes in abstractions.
It’s hard because doing that is at the edge developmentally of young adults...but it’s like giving them a Ferrari as a present for their drivers licenses when we teach this stuff. If experts can’t do it right, think about the implications of teaching them to 19 year olds.
- iujjkfjdkkdkf 6y agoBut will taking away abstractions address what the paper is talking about? If we can abstract away the models and training, I see an opportunity to focus more of the dataset. If you look at something like Pytorch Lightning (and I think fast.ai but am not familiar) you can deploy very powerful, and proven, models without having to get into the details. What might still be missing are more tools to work with the dataset - easily varying size, composition, using active learning, etc. But it's all supported by more abstraction. (I'm a huge believer in the importance of understanding things from first principles, so I agree with making sure students develop their skills that way. But when it comes to practical work with datasets, abstraction is very important)
- avs733 6y agoAt a professional level not directly, but I believe (opinion statement) starting with the abstractions and the abstractions being the focus of all the coursework you typically take contributes to the problem over the long haul.
- selimthegrim 6y agoI'm a firm believer Blockpad (https://blockpad.net https://blockpad.net) can be a powerful Excel-like tool in these environments, especially with engineering data.
- avs733 6y agoWoah...was not familiar with this...
- selimthegrim 6y agoI can tell you Tulane uses their stuff on an education license.
- techdragon 6y agoWow, never seen this before, it looks awesome but the pricing is a bit steep when I compare it to the greater power (but less purpose driven focus) that I have with CoCalc (https://cocalc.com/ https://cocalc.com/) giving me nearly instant, cloud hosted hosted Jupyter notebooks wherever I want them.
- selimthegrim 6y agoI'm sure they're open to feedback!