
Manifold: A model-agnostic visual debugging tool for machine learning (2019) - pplonski86
https://eng.uber.com/manifold
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dennisy
Reading that whole post just looking forward to the github link.

I was sorely disappointed ️

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yanovskishai
[https://github.com/uber/manifold](https://github.com/uber/manifold)

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joelthelion
One thing that seems to be missing is a way to straightforwardly look at
individual examples of data points in each cluster. Oftentimes looking at a
few images (if that's what you're classifying) helps a lot more than staring
at feature distribution plots.

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yanovskishai
It was exactly what I thought. Especially they explicitly say

>"With Manifold’s design, we turned the traditional ML model visualization
challenge on its head. Instead of inspecting models, we inspect individual
data points "

It really seems that they went on implanting the more sophisticated step
(which seems very promising), while skipping the straight forward one.

What am I missing?

