Training a Deep Neural Network in a Spreadsheet
Channel: Kevin Lubick
Date: 2021-08-22

This is Part 2 in a series in which we create and train a neural network in a spreadsheet. This covers Gradient Descent Backpropagation for a deep (2 layer) neural network that learns the XOR function.

Part 1: https://www.youtube.com/watch?v=fjfZZ6S1ad4

Sheets Template:
https://bit.ly/NNsheet

Geogebra plot:
https://www.geogebra.org/3d/uzzwedjb

More information on the Backpropagation Algorithm:
https://www.youtube.com/watch?v=tIeHLnjs5U8
http://neuralnetworksanddeeplearning.com/chap2.html

Building a neural network in C++:
https://markm208.github.io/cppbook/chapter12/02/playback.html?view=code

Narration by James K. Script and visualizations by Kaylee L.

0:00 Intro
0:25 XOR function overview
0:36 Trying to teach a single layer neural network the XOR function
2:07 Why our network failed to learn the XOR function
3:33 Building a deep neural network for the XOR function
6:57 Exploring the weights and biases of a deep neural network
10:07 Visualizing the solution to the deep neural network
11:32 Revisiting the gradient descent formulas
12:23 Implementing "deep" gradient descent in our spreadsheet
21:30 Using copy/paste to iteratively train the network
23:31 Recap

Full playlist of various Neural Networks in Spreadsheets: https://www.youtube.com/watch?v=fjfZZ6S1ad4&list=PLDs5gxU1J5CIt5kIiQLC3RBOAKnUAo412