Use cases / Data Science
Cluster analysis
Build an interactive frontend around the K-means clustering algorithm using Hex, in minutes. Scale, reduce, and encode your features using Python— and then create an interactive app using input parameters.
Create no code visualizations of clusters with the click of a button and when you're done, simply hit the publish to share your work.
Watch demo(1 min)
Explore a live demo
What you can build (app)
How it's built (logic)
Full screen
See what else you can build
Non-linear dimensionality reduction
Visualize high dimensional data using non-linear reduction techniques
Linear Dimensionality Reduction
Visualize high dimensional data using linear reduction techniques
Time series analysis in Snowpark
Forecast hourly restaurant traffic using UDTFs in Snowpark
Ready to get started?
You can use Hex in two ways: our centrally-hosted Hex Cloud stack, or a private single-tenant VPC.