openTSNE: A Modular Python Library for t-SNE Dimensionality Reduction and Embedding

Abstract

One of the most popular techniques for visualizing large, high-dimensional data sets is t-distributed stochastic neighbor embedding (t-SNE). Recently, several extensions have been proposed to address scalability issues and the quality of the resulting visualizations. We introduce openTSNE, a modular Python library that implements the core t-SNE algorithm and its many extensions. The library is faster than existing implementations and can compute projections of data sets containing millions of data points in minutes.