Update your algorithms with confidence

Regression testing

Improve model throughput

ML models evolve fast. Either you are using third party or custom, in-house built algorithms, new features have to be included quickly in order to stay on top of the competition. Such a short release cycle requires an efficient test framework to verify that the algorithm quality increases over time.

Typical regression tools are not a good fit when verifying model quality. This lack of functionality leads to either superficial testing or very time consuming manual procedures. The monitoring functionality of Yields can also be used to compare different versions of a model, to detect possible regression issues and quantify the progress. With Yields, you will know for the impact of a version upgrade before you push the algorithm to production.

Who is it for

Project managers who need to de-risk analytics centered projects.

Managers seeking to measure and report progress on quantitative models

Businesses looking to shorten their analytics development cycle

QA testing teams who want to boost their throughput

Benefits to your business

Faster analytics test cycles leading to more frequent releases and shorter time to market

Parallel detection of algorithmic regression issues

Full reproducibility of discovered problems

Integral part of your continuous integration workflow

One central location where all the test data is available

Interested in a demo?

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