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2022-05-23

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Enhancements

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New Performance Metric: Symmetric Mean Absolute Percentage Error (sMAPE)

Arize users can now use Symmetric Mean Absolute Percentage Error as an accuracy metric for performance tracing. sMAPE is useful when your model is prone to over forecasting, and the shortcomings of MAPE become prohibitive for evaluating accuracy.Learn how sMAPE is calculated here.
Support Latent Tags On ActualsArize users can now log latent actuals with tags. This enables users with delayed actuals to group, monitor, slice, and investigate the performance of delayed cohorts. Latent tags broadens the scope of our existing metadata monitoring features for more comprehensive ML observability.Learn more about how to use tags here.

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In the News

Arize AI Named To Forbes AI 50 List For Second Consecutive YearForbes debuted its AI 50 list** **earlier this month, with Arize recognized for the second consecutive year! Arize is the only machine learning observability platform to make the cut and is named alongside category-leaders and heavyweights like 6sense, Anyscale, Databricks, Dataiku, Generate Biomedicines, Hugging Face, and others. Read the release.
The Seven Habits of Highly Effective ML EngineersWhile there are a wealth of articles and resources geared toward helping people prepare for software engineering jobs, there are relatively few guides to help prospective founding engineers. Arize founding engineer, Manisha Sharma, set out to change that in her latest piece titled “The Seven Habits of Highly Effective Founding Engineers.” Read more.
Rise of the ML Engineer: Elizabeth Hutton, CiscoElizabeth Hutton is the lead machine learning engineer on the Cisco Webex Contact Center AI team, where her work is relied on to provide good customer experiences across billions of monthly calls.** **In this wide-ranging Q&A, Hutton talks about how she got into the industry, best practices for NLP models, and the company’s ML tech stack. Read it.