H2O.ai Room for Improvement

Rahul Koduru
Director of Data Engineering at Transamerica
The model management features could be improved. View full review »
ArnabSen
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. View full review »
MvpOfMac4841
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. View full review »
Find out what your peers are saying about H2O.ai, Knime, Microsoft and others in Data Science Platforms. Updated: February 2020.
398,259 professionals have used our research since 2012.
Mustafa Kirac
Principal Data Scientist
Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive. View full review »
DataScie1afc
Data Scientist with 51-200 employees
I would like to see more features related to deployment. View full review »
reviewer1007100
Supervisor in Research and Development Area with 1,001-5,000 employees
Feature engineering. View full review »
Jaideep Kekre
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. View full review »
Find out what your peers are saying about H2O.ai, Knime, Microsoft and others in Data Science Platforms. Updated: February 2020.
398,259 professionals have used our research since 2012.