Neural Network w/ Javascript

This project was meant for learning purposes only. I wanted to understand how a NN worked, and how i could build one of my own.

My goal with this project.

• Learn how a neuralnetwork works.
• Understand the basic math that surrounds neuralnets.

I started by learning about matrix calculations and how they are used within neural networks. After building my own very basic version of NumPy (matrix) i started reading up on how i could use matrices to represent nodes in a network. How dot operation worked, and how to feed data to a network. After this i started with the difficult part, backpropagation. This took awhile for me to grasp and understand because i lack the intermediate math skills of calculus. Slowly but surely i started to fit the pieces together and successfully built this simple XOR neural network from scratch in javascript. Im happy to share this project even though i would like to expand on it further.

This is my first XOR Neural Network - 100% coded in Javascript.

Tools

• Matrix library (Built from scratch)
• XOR NN (Build from scratch)
• Logging

Everything is created from scratch.

The closed the output (result) is to the target, the more accurate it is to predict the outcome.

These guides help me with this project.

• https://medium.com/@14prakash/back-propagation-is-very-simple-who-made-it-complicated-97b794c97e5c
• https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/
• http://stevenmiller888.github.io/mind-how-to-build-a-neural-network/

My CV

Link to my CV