In order for a model to make the right prediction, you want to make sure the data it receives has the right structure. Scikit-learn does this by allow folks to write pipelines that combine preprocessing with a machine learning model. These pipelines can get elaborate, but that's also the beauty of it. That's why we'll be discussing elaborate pipelines in the next few videos.
00:00 Introduction
01:15 Encoding Titanic
03:17 Starting Small
06:54 make_pipeline
08:22 More elaborate
11:25 Nested union
14:59 Appreciation
save
To learn more about scikit-learn pipelines, you may appreciate this guide:
scikit-learn.org/stable/modul...
The code for all of our videos can be found on this Github repository:
github.com/probabl-ai/youtube...
The code for this specific episode can be found here:
github.com/probabl-ai/youtube...
If you're keen to see more videos like this, you can follow us over at @probabl_ai
Негізгі бет Building Elaborate Pipelines: Part 1
Пікірлер: 5