We performed a comparison between H2O.ai and Microsoft Azure Machine Learning Studio based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."AutoML helps in hands-free initial evaluations of efficiency/accuracy of ML algorithms."
"Fast training, memory-efficient DataFrame manipulation, well-documented, easy-to-use algorithms, ability to integrate with enterprise Java apps (through POJO/MOJO) are the main reasons why we switched from Spark to H2O."
"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."
"It is helpful, intuitive, and easy to use. The learning curve is not too steep."
"The ease of use in connecting to our cluster machines."
"One of the most interesting features of the product is their driverless component. The driverless component allows you to test several different algorithms along with navigating you through choosing the best algorithm."
"It's a great option if you are fairly new and don't want to write too much code."
"The learning curve is very low. Operationalizing the model is also very easy within the Azure ecosystem."
"The AutoML is helpful when you're starting to explore the problem that you're trying to solve."
"The solution is scalable."
"The product's standout feature is a robust multi-file network with limited availability."
"It has helped in reducing the time involved for coding using R and/or Python."
"It helps in building customized models, which are easy for clients to use."
"The most valuable feature is data normalization."
"It lacks the data manipulation capabilities of R and Pandas DataFrames. We would kill for dplyr offloading H2O."
"It needs a drag and drop GUI like KNIME, for easy access to and visibility of workflows."
"Referring to bullet-3 as well, H2O DataFrame manipulation capabilities are too primitive."
"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."
"The model management features could be improved."
"I would like to see more features related to deployment."
"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."
"The speed of deployment should be faster, as should testing."
"The solution's initial setup process is complicated."
"In terms of improvement, I'd like to have more ability to construct and understand the detailed impact of the variables on the model. Their algorithms are very powerful and they explain overall the net contribution of each of the variables to the solution. In terms of being able to say to people "If you did this, you'll get this much more improvement" it wasn't great."
"Microsoft should also include more examples and tutorials for using this product."
"The data cleaning functionality is something that could be better and needs to be improved."
"I think it should be made cheaper for certain people…It may appear costlier for those who don't consider time important."
"The price could be improved."
"While ML Studio does give you the ability to run a lot of transformations, it struggles when the transformations are a bit more complex, when your entire process is transformation-heavy."
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H2O.ai is ranked 19th in Data Science Platforms while Microsoft Azure Machine Learning Studio is ranked 2nd in Data Science Platforms with 49 reviews. H2O.ai is rated 7.6, while Microsoft Azure Machine Learning Studio is rated 7.6. The top reviewer of H2O.ai writes "It is helpful, intuitive, and easy to use. The learning curve is not too steep". On the other hand, the top reviewer of Microsoft Azure Machine Learning Studio writes "Good support for Azure services in pipelines, but deploying outside of Azure is difficult". H2O.ai is most compared with Databricks, Amazon SageMaker, Dataiku Data Science Studio, KNIME and IBM Watson Studio, whereas Microsoft Azure Machine Learning Studio is most compared with Databricks, Google Vertex AI, Azure OpenAI, TensorFlow and Google Cloud AI Platform.
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