We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"The most valuable features are the machine learning tools, the support for Jupyter Notebooks, and the collaboration that allows you to share it across people."
"Personally for me, because I do a lot of development, I like that it is easy to test mathematical algorithms with several matrix calculations. It's perfect for that."
"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."
"To make use of the GPU, you have to have an Nvidia card. What I would want it to do is to run in Next Generation with Intel or AMD, and not just with Nvidia."
"We have a single user license. Support and add-ons are an extra fee."
H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O’s supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models. The H2O platform is used by over 14,000 organizations globally and is extremely popular in both the R & Python communities.
H2O.ai is ranked 14th in Data Science Platforms with 1 review while MathWorks Matlab is ranked 15th in Data Science Platforms with 1 review. H2O.ai is rated 7.0, while MathWorks Matlab is rated 8.0. The top reviewer of H2O.ai writes "Good collaboration functionality, but better integration with Python for data science is needed". On the other hand, the top reviewer of MathWorks Matlab writes "Test run my algorithms with ease before I develop the full software application". H2O.ai is most compared with KNIME, Dataiku Data Science Studio, Amazon SageMaker, Microsoft Azure Machine Learning Studio and SAS Enterprise Miner, whereas MathWorks Matlab is most compared with IBM SPSS Statistics, Microsoft Azure Machine Learning Studio, Anaconda, Databricks and RapidMiner.
See our list of best Data Science Platforms vendors.
We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.