In this live stream, I begin the long process of building a neural network library. I cover the concept of a “multi-layer perceptron” as well as linear algebra / matrix math.

Edited videos coming soon!

30:13 – Intro to Neural Networks
41:38 – Multilayered Perceptron Part 1
1:08:18 – Multilayered Perceptron Part 2
1:48:20 – Linear Algebra for Neural Networks Part 1
2:18:28 – Linear Algebra for Neural Networks Part 2
2:37:00 – Conclusion/Q&A

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Links discussed in this video:
O’Reilly AI Conference:
My Simple Artificial Neural Network JavaScript Library:
Programming from A to Z:
The Nature of Code:
Hadamard product (matrices) on Wikipedia:
Brendan Fortuner’s Linear algebra cheat sheet for deep learning:
this.dot song:
Perceptron video:
NYU Tisch School of the Arts:
ITP – Interactive Telecommunications Program – NYU:
kwichmann’s Learning XOR with a neural net:
Khan Academy’s Linear Algebra class:
3Blue1Brown’s Essence of Linear Algebra:

Books discussed in this video:
Tariq Rashid’s Make Your Own Neural Network:
Marvin Minsky’s Perceptrons:

My Videos mentioned in this video:
Programming from A to Z playlist:
AND and OR:
Playlist on Vectors:
Dot Product:
Nature of Code Playlist:

Source Code for the all Video Lessons:

p5.js:
Processing:

For an Introduction to Programming:
For my Nature of Code videos:
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For More Coding Challenges:

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