tSNEJS is an implementation of t-SNE visualization algorithm in Javascript. Check out the main repo https://github.com/karpathy/tsnejs

t-SNE is a visualization algorithm that embeds things in 2 or 3 dimensions. If you have some data and you can measure their pairwise differences, t-SNE visualization can help you identify clusters in your data. See example below.

In this project I used the images from the result of train process of DCGAN machine learning algorithm and the discriminator and generator loss values as the 2 dimensional data points from 100 epocs to be able to see the similarities between the images generated over time. In a sense, I indended to use tSNE visualization to be able to get more involved in the learning process of an algorithm in an interactive way.

Deep Convolutional Generative Adversarial Networks (GANs) is a class of unsupervised machine learning framework where two models are trained simultaneously by an adversarial process. A generator ("the artist") learns to create images that look real, while a discriminator ("the art critic") learns to tell real images apart from fakes. I used one of the implementations of DCGAN to generate the images for this project: https://github.com/tensorlayer/dcgan

The main project website has a live example and more description.

There is also the t-SNE CSV demo that allows you to simply paste CSV data into a textbox and tSNEJS computes and visualizes the embedding on the fly (no coding needed).