H2O.ai vs SAS Visual Data Mining and Machine Learning comparison

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1,962 views|1,376 comparisons
100% willing to recommend
Executive Summary

We performed a comparison between H2O.ai and SAS Visual Data Mining and Machine Learning based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms.
To learn more, read our detailed Data Science Platforms Report (Updated: May 2024).
771,170 professionals have used our research since 2012.
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Pricing and Cost Advice
  • "We have seen significant ROI where we were able to use the product in certain key projects and could automate a lot of processes. We were even able to reduce staff."
  • More H2O.ai Pricing and Cost Advice →

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    Ranking
    20th
    Views
    1,962
    Comparisons
    1,376
    Reviews
    0
    Average Words per Review
    0
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    26th
    Views
    424
    Comparisons
    383
    Reviews
    0
    Average Words per Review
    0
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    N/A
    Buyer's Guide
    Data Science Platforms
    May 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: May 2024.
    771,170 professionals have used our research since 2012.
    Comparisons
    Also Known As
    Visual Data Mining and Machine Learning
    Learn More
    Overview

    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.

    SAS Visual Data Mining and Machine Learning combines data wrangling, data exploration, visualization, feature engineering, and modern statistical, data mining and machine learning techniques all in a single, scalable in-memory processing environment. This provides faster, more accurate answers to complex business problems, increased deployment flexibility and one easy-to-administer and fluid IT environment.

    Sample Customers
    poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
    Information Not Available
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company11%
    Manufacturing Company9%
    Insurance Company6%
    VISITORS READING REVIEWS
    Financial Services Firm18%
    Computer Software Company18%
    Manufacturing Company10%
    Insurance Company9%
    Company Size
    REVIEWERS
    Small Business22%
    Midsize Enterprise22%
    Large Enterprise56%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise69%
    VISITORS READING REVIEWS
    Small Business17%
    Midsize Enterprise10%
    Large Enterprise74%
    Buyer's Guide
    Data Science Platforms
    May 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: May 2024.
    771,170 professionals have used our research since 2012.

    H2O.ai is ranked 20th in Data Science Platforms while SAS Visual Data Mining and Machine Learning is ranked 26th in Data Science Platforms. H2O.ai is rated 7.6, while SAS Visual Data Mining and Machine Learning is rated 0.0. 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, H2O.ai is most compared with Databricks, Amazon SageMaker, Dataiku, Microsoft Azure Machine Learning Studio and KNIME, whereas SAS Visual Data Mining and Machine Learning is most compared with SAS Visual Analytics, Databricks, SAS Enterprise Miner and Microsoft Azure Machine Learning Studio.

    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.