What do you think about whether to do first unsupervised learning or first model selection?
In 2013 they did first supervised learning, examples, grid-search, and then unsupervised learning.
In the outline I proposed, we'd do both supervised and unsupervised learning in the beginning, and then cross-validation and grid-searches etc.
Do you have a preference?
As we have quite a bit of time, I think it would be nice to start the whole thing by explaining the different kinds of learning, that is supervised, unsupervised, (maybe reinforcement) roughly, and then say that sklearn does both supervised and unsupervised and show the API.
What do you think about whether to do first unsupervised learning or first model selection?
In 2013 they did first supervised learning, examples, grid-search, and then unsupervised learning.
In the outline I proposed, we'd do both supervised and unsupervised learning in the beginning, and then cross-validation and grid-searches etc.
Do you have a preference?
As we have quite a bit of time, I think it would be nice to start the whole thing by explaining the different kinds of learning, that is supervised, unsupervised, (maybe reinforcement) roughly, and then say that sklearn does both supervised and unsupervised and show the API.