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Visual Machine Learning and Modeling

Dataiku makes it easy to leverage machine learning technologies and get instant visual and statistical feedback on model performance.
Automated machine learning
  • Automatic feature engineering, generation, and selection to use any kind of data in your models.

  • Optimize your model hyperparameters using various cross validation strategies.

  • Compare dozens of algorithms from Dataiku interface, both for supervised and unsupervised tasks.

  • Get instant visual insights from your model (variables importance, features interactions or parameters), and assess model’s performance through detailed metrics.

Deep learning at your fingertips
  • Define your model architecture and personalize training settings.

  • Support for Keras, Tensorflow backend, integrate with Tensorboard, and scale model training using GPU.

  • Automatically handle images, including features extraction.

  • Use pretrained models right from Dataiku interface

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 lifecycle: deploy new versions, retrain previous versions and rollback to any secure version in just one click.

  • Control your model’s performance over time with a feedback loop.

Use visual UI or code to leverage the latest ML technologies
  • The visual machine learning in Dataiku leverages state-of-the-art machine learning libraries: Scikit-Learn, MLlib, XGboost.

  • Create, train and deploy advanced custom ML models using Python or R.

  • Integrate any external machine learning library accessible through code APIs.

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