H2O.ai Room for Improvement

RK
Director of Data Engineering at Transamerica

The model management features could be improved.

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DC
Managing VP of Machine Learning at a financial services firm with 10,001+ employees

The interpretability module has room for improvement. Also, it needs to improve its ability to integrate with other systems, like SageMaker, and the overall integration capability.

I would like more support for scalability and deep learning. Right now, they are very strong in supervise and supervise learning, but not in deep learning. I'd like to see them be more well-rounded, where they have support for deep learning, but I'm not sure that is their business model.

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AS
Associate Principal at a consultancy with 501-1,000 employees

On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time. It becomes a problem.

I would like to see better integration with Python and data science capabilities.

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Buyer's Guide
Data Science Platforms
April 2024
Find out what your peers are saying about H2O.ai, Knime, Dataiku and others in Data Science Platforms. Updated: April 2024.
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it_user837546 - PeerSpot reviewer
Principal Data Scientist

Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive.

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it_user862530 - PeerSpot reviewer
Associate Consultant at a tech services company with 201-500 employees

It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows.

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DR
Supervisor in Research and Development Area with 1,001-5,000 employees

Feature engineering.

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MH
Data Scientist with 51-200 employees

I would like to see more features related to deployment.

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Buyer's Guide
Data Science Platforms
April 2024
Find out what your peers are saying about H2O.ai, Knime, Dataiku and others in Data Science Platforms. Updated: April 2024.
769,599 professionals have used our research since 2012.