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My partner has ditched crosstraining into data science and ML because of how ridiculously 'ductape and string' the entire sub-indistry is. Tooling that is pre-2
by weego 7y ago
My partner has ditched crosstraining into data science and ML because of how ridiculously 'ductape and string' the entire sub-indistry is. Tooling that is pre-2000 quality if it even exists, people with math skills yet only the most rudimentary ability in best practice around data storage and maintenance, coding, domain knowledge and understanding of how much bias they're introducing into results. Her view is its just a free for all of people who have little to no need to justify their output because everyone is waiting and hoping for the magic to happen.
- deleted 7y ago[deleted]
- itronitron 7y agoLarger organizations (by size and longevity) tend to have staff that predate the data science and ML/AI hype train and have therefore worked out more robust tooling. Unfortunately the popularity of ML is driving a lot of adoption of trendy but not necessarily best practices.
- mattlutze 7y agoThere was a lot of this sort of thing with the web application boom as well. Lots and lots of decrying how JS libraries and frameworks were ruining the software industry. I've not following that very much in a decade though. Did that whole area end up maturing?