3 ms·
Wouldn't call the ensembling of xgboost models + catboost "little effort". One thing that is true however is that xgboost will usually give better performance w
by halflings 8y ago
Wouldn't call the ensembling of xgboost models + catboost "little effort".
One thing that is true however is that xgboost will usually give better performance without tuning, vs DNNs without any tuning / hyperparameter search.
- autokad 8y agopsudocode here: yhat_xgboost = xg.predict(x_test) y_hat_cat = cat.predict(x_test) y_hat = .7 * y_hat_xgboost + .3 * y_hat_cat how is that not little effort?
- namuol 8y agoI really think the FastAI course needs to be taken with a heaping dose of salt in the form of "here are all the non-DL solutions to common problems" -- there's a ton of material out there already, but based on anecdotal evidence, there are a lot of folks very new to ML & data science in general that are taking the course (i.e. people like myself).
- harveynick 8y agoHave you looked at fast.ai's ML course? It might also be worth a try. http://forums.fast.ai/t/another-treat-early-access-to-intro-to-machine-learning-videos/6826 http://forums.fast.ai/t/another-treat-early-access-to-intro-... I'd also recommend the Andrew Ng Coursera course, which I talked about here: https://harveynick.com/2018/04/25/some-notes-on-the-andrew-ng-coursera-machine-learning-course/ https://harveynick.com/2018/04/25/some-notes-on-the-andrew-n...