September 7th, 2018

Key Takeaways from the Forrester Notebook Wave

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The Forrester Wave: Notebook-Based Predictive Analytics and Machine Learning Solutions, Q3 2018 is out, and H2O.ai is a Strong Performer! The report looks at machine learning platforms centered on R and Python languages using notebooks like Jupyter and Zeppelin. Vendors are evaluated along three dimensions including market presence, current offering, and overall strategy.

Here are some key takeaways –

Broad Adoption of H2O Algorithms

H2O.ai had the highest rating for market presence comparable to Google and has more market awareness than players like Oracle, OpenText, Databricks and others. For the current offering, there should be little surprise that H2O-3 and H2O Sparkling Water are the top performers in open source algorithms. Forrester even acknowledges that many other machine learning vendors integrate the H2O algorithms into their platforms.

Top Scores for Product Strategy

H2O.ai gets the highest score of any vendor in the report for overall product strategy with three perfect scores out of the five evaluation criteria in Driverless AI product which automates large swaths of the data science lifecycle to automatically build hundreds or even thousands of models.”

Automatic Machine Learning Wave Next Year

Forrester Research has recognized that the market for AI and ML platforms is evolving rapidly. In this report, they announced the creation of three separate Wave reports for the machine learning space including two on Notebook based solutions and the third Wave on automatic machine learning. The production of a separate report is excellent news for H2O.ai as an innovator in the automatic machine learning space with H2O Driverless AI. Keep an eye out for the new automation focused Wave next year.

About the Author

vinod iyengar
Vinod Iyengar, VP of Products

Vinod is VP of Products at H2O.ai. He leads all product marketing efforts, new product development and integrations with partners. Vinod comes with over 10 years of Marketing & Data Science experience in multiple startups. He was the founding employee for his previous startup, Activehours (Earnin), where he helped build the product and bootstrap the user acquisition with growth hacking. He has worked to grow the user base for his companies from almost nothing to millions of customers. He’s built models to score leads, reduce churn, increase conversion, prevent fraud and many more use cases. He brings a strong analytical side and a metrics driven approach to marketing. When he is not busy hacking, Vinod loves painting and reading. He is a huge foodie and will eat anything that doesn’t crawl, swim or move.

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