3 ms·
Just out of curiosity where do you see the demand? I've also heard from others that there's been a shift lately towards simpler models. Combined with domain kno
by figurative 4y ago
Just out of curiosity where do you see the demand? I've also heard from others that there's been a shift lately towards simpler models. Combined with domain knowledge linear/logistic regression can be really impressive!
- dbs 4y ago> Combined with domain knowledge linear/logistic regression can be really impressive! Can you elaborate?
- rmnclmnt 4y agoI can agree this the comment. Linear models combined with advanced feature engineering gathered from domain knowledge can achieve great results in a white-box fashion! A nice keynote by Vincent Warmerdam [1] talks about tips and tricking for advanced feature engineering combined with linear models. [1] https://www.youtube.com/watch?v=68ABAU_V8qI https://www.youtube.com/watch?v=68ABAU_V8qI
- beckingz 4y agoA significant portion of ML workloads involve predicting or classifying something. Linear/logistic regression of the right variables/features typically gets a significant portion of the data's ability to predict /classify correctly, while being significantly easier to build, train, deploy, and understand. Heck, in a large number of domains, simple ratios -- debt to income ratio in finance for example -- will dominate the feature weight for many models and can be used on their own as a pretty good heuristic.
- rmnclmnt 4y agoSmall non-FAANG companies usually, where they do not have the internal skills to maintain and explain models. And from what I've heard, big corporations under regulated domains (banking, healthcare, etc).