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Posted by surprisetalk 3 days ago

Understanding Neural Network, Visually(visualrambling.space)
188 points | 24 commentspage 2
4fterd4rk 8 hours ago||
Great explanation, but the last question is quite simple. You determine the weights via brute force. Simply running a large amount of data where you have the input as well as the correct output (handwriting to text in this case).
ggambetta 7 hours ago|
"Brute force" would be trying random weights and keeping the best performing model. Backpropagation is compute-intensive but I wouldn't call it "brute force".
Ygg2 7 hours ago||
"Brute force" here is about the amount of data you're ingesting. It's no Alpha Zero, that will learn from scratch.
jazzpush2 4 hours ago||
What? Either option requires sufficient data. Brute force implies iterating over all combinations until you find the best weights. Back-prop is an optimization technique.
artemonster 4 hours ago||
I get 3fps on my chrome, most likely due to disabled HW acceleration
nerdsniper 4 hours ago|
High FPS on Safari M2 MBP.
anon291 5 hours ago||
Nice visuals, but misses the mark. Neural networks transform vector spaces, and collect points into bins. This visualization shows the structure of the computation. This is akin to displaying a Matrix vector multiplication in Wx + b notation, except W,x,and b have more exciting displays.

It completely misses the mark on what it means to 'weight' (linearly transform), bias (affine transform) and then non-linearly transform (i.e, 'collect') points into bins

titzer 4 hours ago|
> but misses the mark

It doesn't match the pictures in your head, but it nevertheless does present a mental representation the author (and presumably some readers) find useful.

Instead of nitpicking, perhaps pointing to a better visualization (like maybe this video: https://www.youtube.com/watch?v=ChfEO8l-fas) could help others learn. Otherwise it's just frustrating to read comments like this.

pks016 5 hours ago||
Great visualization!
javaskrrt 6 hours ago|
very cool stuff