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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    H2O.ai

    Score6.4 out of 10
    N/AAn open-source end-to-end GenAI platform for air-gapped, on-premises or cloud VPC deployments. Users can Query and summarize documents or just chat with local private GPT LLMs using h2oGPT, an Apache V2 open-source project. And the commercially available Enterprise h2oGPTe provides information retrieval on internal data, privately hosts LLMs, and secures data.N/A

    JMP Pro

    Score6 out of 10
    N/AJMP Pro offers all the capabilities of JMP, plus advanced features for more sophisticated analysis including predictive modeling and cross-validation techniques.N/A
    Pricing
    H2O.aiJMP Pro
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    H2O.aiJMP Pro
    Free Trial
    NoNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Best Alternatives
    H2O.aiJMP Pro
    Small Businesses
    Saturn Cloud
    Score7.8 out of 10
    No answers on this topic
    Medium-sized Companies
    DataRobot
    Score8.2 out of 10
    SAS Enterprise Guide
    Score9.4 out of 10
    Enterprises
    DataRobot
    Score8.2 out of 10
    SAS Enterprise Guide
    Score9.4 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    H2O.aiJMP Pro
    Likelihood to Recommend
    8.1
    (3 ratings)
    7.0
    (3 ratings)
    Usability
    -
    (0 ratings)
    6.0
    (1 ratings)
    Support Rating
    9.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    H2O.aiJMP Pro
    Likelihood to Recommend
    H2O.ai
    Most suited if in little time you wanted to build and train a model. Then, H2O makes life very simple. It has support with R, Python and Java, so no programming dependency is required to use it. It's very simple to use. If you want to modify or tweak your ML algorithm then H2O is not suitable. You can't develop a model from scratch.
    Incentivized
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    JMP Statistical Discovery
    JMP Pro is perfectly suited for statistical analysis but users should have some statistical knowledge before using it since there may be some terms/functions in the software that are not widely used in other fields. No prior coding experience is needed to use JMP Pro. However, most people doing data processing would prefer to code their analysis.
    Incentivized
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    Pros
    H2O.ai
    • Excellent analytical and prediction tool
    • In the beginning, usage of H20 Flow in Web UI enables quick development and sharing of the analytical model
    • Readily available algorithms, easy to use in your analytical projects
    • Faster than Python scikit learn (in machine learning supervised learning area)
    • It can be accessed (run) from Python, not only JAVA etc.
    • Well documented and suitable for fast training or self studying
    • In the beginning, one can use the clickable Flow interface (WEB UI) and later move to a Python console. There is then no need to click in H20 Flow
    • It can be used as open source
    Incentivized
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    JMP Statistical Discovery
    • Several types of segmentation models
    • Conjoint design
    • VERY user-friendly
    Incentivized
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    Cons
    H2O.ai
    • Better documentation
    • Improve the Visual presentations including charting etc
    Incentivized
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    JMP Statistical Discovery
    • JMP Pro is a really powerful tool for doing statistical analysis. Although the click environment does not require coding experience, new learners will still need to take a long time to know the parameters in the function before performing any analysis.
    • The output from JMP Pro analysis (regression analysis) is not always easy to understand, especially when the parameters are programmed differently with the other similar software.
    Incentivized
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    Usability
    H2O.ai
    No answers on this topic
    JMP Statistical Discovery
    JMP Pro is a great tool, but it's not user friendly. JMP Pro is something that requires a lot of trial and error to figure out. Minitab is far more user friendly and their help guides walk new users how to do everything. JMP Pro requires taking the time to do the STIPs course, or brute force figuring it out.
    Incentivized
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    Support Rating
    H2O.ai
    The overall experience I have with H2O is really awesome, even with its cost effectiveness.
    Incentivized
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    JMP Statistical Discovery
    No answers on this topic
    Alternatives Considered
    H2O.ai
    Both are open source (though H2O only up to some level). Both comprise of deep learning, but H2O is not focused directly on deep learning, while Tensor Flow has a "laser" focus on deep learning. H2O is also more focused on scalability. H2O should be looked at not as a competitor but rather a complementary tool. The use case is usually not only about the algorithms, but also about the data model and data logistics and accessibility. H2O is more accessible due to its UI. Also, both can be accessed from Python. The community around TensorFlow seems larger than that of H2O.
    Incentivized
    Read full review
    JMP Statistical Discovery
    I use both JMP Pro and Minitab. JMP Pro works great for doing the work that needs live edit functionable, and the ability to filter charts on the go. Minitab is what I use for capability analysis and MSAs as the overall UI is much cleaner, and is far nicer to present to management than JMP Pro.
    Incentivized
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    Return on Investment
    H2O.ai
    • Positive impact: saving in infrastructure expenses - compared to other bulky tools this costs a fraction
    • Positive impact: ability to get quick fixes from H2O when problems arise - compared to waiting for several months/years for new releases from other vendors
    • Positive impact: Access to H2O core team and able to get features that are needed for our business quickly added to the core H2O product
    Incentivized
    Read full review
    JMP Statistical Discovery
    • None. It's cheaper than SPSS. You could probably get by with the basic JMP package.
    Incentivized
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