Hello,
We're contributors to the open source project Metacademy (
http://www.metacademy.org http://github.com/metacademy), which is creating
a curated web of machine learning concepts. The idea is that Metacademy can
tell users how to efficiently learn a concept and all of its necessary
prerequisites given their current knowledge. One of the motivations for
this project was to help practitioners with varying backgrounds learn the
intricacies of the algorithms they use (without spending a few months
taking an online course or a few thousand dollars taking a traditional
one).
Here's a quick example of a learning plan:
http://metacademy.org/graphs/concepts/logistic_regression
(click the graph button in the upper right to visualize the prerequsite
structure)
(try clicking a few check marks of the concepts you know and pressing
"hide" in the toolbox in the upper right -- this creates a personalized
learning plan)
We thought adding pointers to metacademy concepts in the SKL documentation
could help interested practitioners gain a deeper understanding of these
concepts. But rather than changing the documentation willy-nilly and making
pull requests, we thought we should contact the current contributors and
see whether they feel this idea could benefit SKL. We currently have over
300 annotated concepts, which covers most of the functionality present in
SKL, and we are happy to add any missing concepts that SKL
users/contributors feel would benefit the documentation.
best wishes
Colorado Reed & Roger Grosse
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