Skip to main content

CUDA Implementation of T-SNE with Python bindings

Project description

tsnecuda provides an optimized CUDA implementation of the T-SNE algorithm by L Van der Maaten. tsnecuda is able to compute the T-SNE of large numbers of points up to 1200 times faster than other leading libraries, and provides simple python bindings with a SKLearn style interface:

#!/usr/bin/env python

from tsnecuda import TSNE
embeddedX = TSNE(n_components=2).fit_transform(X)

For more information, check out the repository at

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for tsnecuda, version 3.0.0
Filename, size File type Python version Upload date Hashes
Filename, size tsnecuda-3.0.0-py3-none-any.whl (53.2 MB) File type Wheel Python version py3 Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page