AI / ML AutoML mature

H2O.ai

Distributed AutoML platform for enterprise machine learning

7.0K stars 200 contributors Since 2012
Website → GitHub

Open-source distributed ML platform with AutoML, model explainability, Sparkling Water for Spark integration, and H2O Flow visual GUI for non-programmers.

License
Apache-2.0
Min RAM
2 GB
Min CPUs
2 cores
Scaling
distributed
Complexity
intermediate
Performance
enterprise grade
Self-hostable
K8s native
Offline
Pricing
fully free
Docs quality
good
Vendor lock-in
none

Use cases

  • AutoML for rapid model selection and hyperparameter tuning
  • Visual ML with H2O Flow for business analysts
  • Spark-based distributed model training
  • Model explainability reports for regulated industries

Anti-patterns / when NOT to use

  • Java-based — heavier than pure Python tools
  • Flow GUI limited for complex pipelines
  • Enterprise features locked behind paid version

Integrates with

Replaces / alternatives to

  • DataRobot
  • Google AutoML
  • Azure AutoML

Technical specs

Language
JavaPythonR
API type
RESTSDK
Protocols
HTTP
Deployment
pipdockerbinary
SDKs
pythonrjavascala

Community

GitHub stars 7.0K
Contributors 200
Commit frequency weekly
Plugin ecosystem medium
Backing H2O.ai
Funding open_core

Release

Latest version
Last release
Since 2012

Best fit

Team size
smallmediumenterprise
Industries
fintechhealthcareinsurancetelecom

Tags

  • automl
  • distributed-ml
  • model-explainability
  • flow-gui
  • spark-integration