Boosting vs. semi-supervised learning

Описание к видео Boosting vs. semi-supervised learning

While gradient boosted algorithms are amazing, they aren't a silver bullet for everything. Especially when you're dealing with a dataset that only has a very small set of labels. For those use-cases you may want to resort to semi-supervised learning techniques instead.

To learn more about label propagation, check the API docs here:
https://scikit-learn.org/stable/modul...

00:00 Describing the edge case
01:35 When classifiers fail
04:03 Semi supervised
09:42 Applied

This whiteboard video is part of the open efforts over at probabl. To learn more you can check out website or reach out to us on social media.

Website: https://probabl.ai/
LinkedIn:   / probabl  
Twitter: https://x.com/probabl_ai

We also host a podcast called Sample Space, which you can find on your favourite podcast player. All the links can be found here:
https://rss.com/podcasts/sample-space/

If you're keen to see more videos like this, you can follow us over at @probabl_ai.

Комментарии

Информация по комментариям в разработке