My submission for 2022 #SoME2. In this video I try to explain what a neural network is in the simplest way possible. That means no linear algebra, no calculus, and definitely no statistics. The aim is to be accessible to absolutely anyone.
00:00 Intro
00:47 Gauss & Parametric Regression
02:59 Fitting a Straight Line
06:39 Defining a 1-layer Neural Network
09:29 Defining a 2-layer Neural Network
Part of the motivation for making this video is to try to dispel some of the misunderstandings around #deeplearning and to highlight 1) just how simple the neural network algorithm actually is and 2) just how NOT like a human brain it is.
I also haven’t seen Gauss’s original discovery of parametric regression presented anywhere before, and I think its a fun story to highlight just how far (and how little) data science has come in 200 years.
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In full disclosure, planets do not orbit in straight lines, and Gauss did not fit a straight line to Ceres’ positions, but rather an ellipse (in 3d).
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