State-of-the-art methods to estimate and explore context-specific models
Comprehensive support for multiple types of models and meta-models, with training and analysis tools
Building blocks to support extending meta-models to contextualize your application-specific mdoel
Access state-of-the-art techniques through an open unified API and rich visualizations.
Understand models using a wide range of explainers and techniques using interactive visuals. PyTorch Choose your algorithm and easily experiment with combinations of algorithms.
Join the community, request and contribute improvements to make your model the best it can be.
Do the features which predict an outcome change from sample to sample?
Does the joint distribution of features change from sample to sample?
Do the correlations between features change from sample to sample?
Understand heterogeneity hiding in your dataset.
Understand heterogenetiy in the observed populations.
Build models which adapt to new environments and contexts.
Contextualize your new models.