Neural Networks in JavaScript with deeplearn.js

A couple of my recent articles gave an introduction into a subfield of artificial intelligence by implementing foundational machine learning algorithms in JavaScript (e.g. linear regression with gradient descentlinear regression with normal equation or logistic regression with gradient descent). These machine learning algorithms were implemented from scratch in JavaScript by using the math.js node package for linear algebra (e.g. matrix operations) and calculus. You can find all of these machine learning algorithms grouped in a GitHub organization. If you find any flaws in them, please help me out to make the organization a great learning resource for others. I intend to grow the amount of repositories showcasing different machine learning algorithms to provide web developers a starting point when they enter the domain of machine learning.

Personally, I found it becomes quite complex and challenging to implement those algorithms from scratch at some point. Especially when combining JavaScript and neural networks with the implementation of forward and back propagation. Since I am learning about neural networks myself at the moment, I started to look for libraries doing the job for me. Hopefully I am able to catch up with those foundational implementations to publish them in the GitHub organization in the future. However, for now, as I researched about potential candidates to facilitate neural networks in JavaScript, I came across deeplearn.js which was recently released by Google. So I gave it a shot. In this article / tutorial, I want to share my experiences by implementing with you a neural network in JavaScript with deeplearn.js to solve a real world problem for web accessibility.
