machine learning

READ DATASHEET
  • Step-by-step guided
    machine learning
  • Scalable and customizable
    machine learning
  • Fully production
    ready
  • Step-by-step guided
    machine learning
  • Scalable and customizable
    machine learning
  • Fully production
    ready

Step-by-step guided machine learning

  • Clean data, create new features, and build your model in a unified environment.
  • Get instant visual feedback to assess your model’s performance.
  • Compare and optimize your models using various cross validation strategies.

Understand your models

  • Immediately see which features have the most impact on your prediction with variable importance.
  • Quickly understand complex feature interactions and analyse coefficients.
  • Automated visual and statistical reports help you interpret the clusters resulting from non-supervised machine learning.

Use Visual UI or Code to Leverage Latest ML Technologies

  • The visual machine learning in DSS leverages state-of-the-art machine learning libraries: Scikit-Learn, MLlib, XGboost.
  • Customize code directly in Python and R for advanced custom machine learning.
  • Integrate any external machine learning library accessible through code APIs (H2O, Dato, Skytree, etc).

Fully production ready

As soon as your model is built and assessed, instantly:

  • Use it for batch scoring within your data workflow.
  • Deploy it as a real-time prediction service (REST API).
  • Manage your model lifetime: save previous versions of a retrained model and rollback to any secure version in just one click.
  • Manage your model's performance with a feedback loop.