Visuals to demonstrate how a neural network classifies a set of data. Thanks for watching!
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Source Code: https://github.com/vivek3141/dl-visua...
Here's the course I referred to in the video. I am not affiliated with NYU.
• NYU Deep Learning SP20
Sinusoids as activation functions:
https://openreview.net/forum?id=Sks3z...
https://vsitzmann.github.io/siren/
Here's the distill.pub article:
https://distill.pub/2020/grand-tour/
Special thanks to Alfredo Canziani and Nikhil Maserang for reviewing the video.
And also thanks to Grant Sanderson himself for giving me some manim tips!
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These animation in this video was made using 3blue1brown's library, manim:
https://github.com/3b1b/manim
Music is from GameChops (Route 113, Azalea Town, Ecruteak City
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What does a Neural Network actually do? Visualizing Deep Learning, Chapter 2
0:00 Intro
0:18 Recap of Part 1
1:57 Introducing the dataset
2:52 Structure of the Neural Network we’ll be using
3:34 What is softmax?
5:52 Input space decision boundaries
6:24 Modifying the Neural Network to visualize what it’s doing
7:36 Out-of-domain boundaries
8:46 sin(x) as an activation function
9:30 Neuron planes
11:57 Softmax surfaces
13:20 MNIST Transformation
13:42 Outro
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