Letsogile-BaloiCEO at IMART OFFICE CONSULTANTS
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."
"The solution is very easy to use."
"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"The scalability of IBM Watson Studio is great."
"The system's ability to take a look at data, segment it and then use that data very differently."
"IBM Watson Studio consistently automates across channels."
"It has a lot of data connectors, which is extremely helpful."
"On the topic of model training and model governance, this solution cannot handle ten or twelve models running at the same time."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"So a better user interface could be very helpful"
"The decision making in their decision making feature is less good than other options."
"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"The initial setup was complex."
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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.
IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.
H2O.ai is ranked 14th in Data Science Platforms with 1 review while IBM Watson Studio is ranked 11th in Data Science Platforms with 6 reviews. H2O.ai is rated 7.0, while IBM Watson Studio is rated 8.2. 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 IBM Watson Studio writes "Machine learning that can be applicable for other data sets without having to carry out the process all over again". H2O.ai is most compared with KNIME, Dataiku Data Science Studio, Amazon SageMaker, Microsoft Azure Machine Learning Studio and Domino Data Science Platform, whereas IBM Watson Studio is most compared with Microsoft Azure Machine Learning Studio, IBM SPSS Modeler, Amazon SageMaker, Google Cloud Datalab and KNIME.
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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.