H2O.ai vs Zepl comparison

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H2O.ai Logo
1,962 views|1,376 comparisons
100% willing to recommend
Zepl Logo
58 views|38 comparisons
Executive Summary

We performed a comparison between H2O.ai and Zepl 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: April 2024).
770,292 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
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 →

    Information Not Available
    Ranking
    20th
    Views
    1,962
    Comparisons
    1,376
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    40th
    Views
    58
    Comparisons
    38
    Reviews
    0
    Average Words per Review
    0
    Rating
    N/A
    Buyer's Guide
    Data Science Platforms
    April 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: April 2024.
    770,292 professionals have used our research since 2012.
    Comparisons
    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.

    Zepl enables data science teams to rapidly explore, analyze and collaborate around their cloud data. In just minutes, Zepl brings machine learning at scale to data scientists, data engineers, data analysts, team managers and executives. Used by high tech, financial services, pharmaceutical, IoT, and automotive companies, Zepl changes the game by automating model-driven insights in a highly secure manner. Zepl rapidly accelerates experimentation, frictionless collaboration, training of ML models, and transforms customers from reactive to proactive enterprises through the use of powerful machine learning insights. Try Zepl for free today at www.zepl.com.

    Sample Customers
    poder.io, Stanley Black & Decker, G5, PWC, Comcast, Cisco
    Samsung, Boulder, American Express, AT & T, Bank-Of-America, Charles Schwab, Cisco, Citi, Comcast
    Top Industries
    VISITORS READING REVIEWS
    Financial Services Firm19%
    Computer Software Company11%
    Manufacturing Company9%
    Insurance Company6%
    No Data Available
    Company Size
    REVIEWERS
    Small Business22%
    Midsize Enterprise22%
    Large Enterprise56%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise12%
    Large Enterprise70%
    No Data Available
    Buyer's Guide
    Data Science Platforms
    April 2024
    Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms. Updated: April 2024.
    770,292 professionals have used our research since 2012.

    H2O.ai is ranked 20th in Data Science Platforms while Zepl is ranked 40th in Data Science Platforms. H2O.ai is rated 7.6, while Zepl 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 Data Science Studio, Microsoft Azure Machine Learning Studio and KNIME, whereas Zepl is most compared with .

    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.