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
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Automatic feature engineering, generation, and selection to use any kind of data in your models.
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Optimize your model hyperparameters using various cross validation strategies.
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Compare dozens of algorithms from Dataiku interface, both for supervised and unsupervised tasks.
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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
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Define your model architecture and personalize training settings.
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Support for Keras, Tensorflow backend, integrate with Tensorboard, and scale model training using GPU.
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Automatically handle images, including features extraction.
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Use pretrained models right from Dataiku interface
Fully production ready
As soon as your model is built and assessed, instantly:
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Use it for batch scoring within your data workflow.
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Deploy it as a real-time prediction service (REST API).
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Manage your model lifecycle: deploy new versions, retrain previous versions and rollback to any secure version in just one click.
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Control your model’s performance over time with a feedback loop.
Use visual UI or code to leverage the latest ML technologies
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The visual machine learning in Dataiku leverages state-of-the-art machine learning libraries: Scikit-Learn, MLlib, XGboost.
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Create, train and deploy advanced custom ML models using Python or R.
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Integrate any external machine learning library accessible through code APIs.
