PyCaret provides a low code AutoML platform for Python, with a scikit-learn native engine and React control plane.
H2O AutoML
H2O AutoML automatically generates features and selections, with a no code AutoML offering.
About H2O AutoML
H2O AutoML automates the steps of building machine learning models, including algorithm selection, feature generation, hyperparameter tuning, iterative modeling, and model assessment. Users can work through R, Python, or a web GUI. The homepage states that training can be scaled to clusters on Hadoop, Spark, and Kubernetes.
The homepage describes H2O AutoML as part of H2O-3 and says that models can be exported for production use. The source does not state pricing, and it does not list specific limits on data size, supported model types, or deployment requirements.
Key features
- Automatic data preprocessing, including imputation, one-hot encoding, and standardization
- Random grid training across a range of H2O models with defined hyperparameter spaces
- Stacked ensembles trained to maximize model performance
- Leaderboard that ranks all models by various metrics
- Automatic model explanations through the H2O Explainability module
- No-code web GUI for selecting AutoML parameters by clicking
Best for: People who want to train and compare machine learning models with less manual code, including users with limited machine learning expertise.
Good for
- Reduces manual code-writing time for building and tuning models
- Supports reproducibility and provides a baseline for research or applications
- Automates repetitive modeling tasks so users can focus on data and business problems
H2O AutoML at a glance
- Website
- h2o.ai/platform/h2o-automl
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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H2O AutoML FAQ
Can I use H2O AutoML without writing code?
Yes. The web GUI allows users to select all of the parameters inside H2O-3, including AutoML, through clicks and selections. R and Python interfaces are also available.
Which interfaces are available for H2O AutoML?
The homepage lists R, Python, and a web GUI.
Can H2O AutoML run on large data clusters?
The homepage states that training data sets can be scaled to clusters, including Hadoop, Spark, and Kubernetes.
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