Testimonials from Google, Wells Fargo, and others:

Case Studies | Cleanlab Technology

Resources:

• Open-Source Growth over time: https://star-history.t9t.io/#cleanlab/cleanlab
• How scientists use Cleanlab: https://scholar.google.com/scholar?q="cleanlab"
• Related news coverage: https://github.com/cleanlab/label-errors#selected-news-coverage

Learn how companies (and you!) use Cleanlab:

Google Senior Software Engineer uses Cleanlab to find data errors at scale:

“Cleanlab is well-designed, scalable and theoretically grounded: it accurately finds data errors, even on well-known and established datasets. After using it for a successful pilot project at Google, Cleanlab is now one of my go-to libraries for dataset cleanup.”
— Patrick Violette, Senior Software Engineer, Google

Berkeley Research Group increases ML model accuracy by 15% and reduces time spent by 1/3 using Cleanlab Studio.

source: https://www.linkedin.com/posts/steven-gawthorpe-b4298118_cleanlab-studio-activity-7009197862525747200-7nnA

Wells Fargo uses cleanlab for accurate financial prediction with 45% label noise

“We tested how well it works on our financial text data. And I can tell you, your Cleanlab works well.”
— Yifei Gong, Analyst Intern, Wells Fargo

**The Stakeholder Company (Singapore) saves 8x time with Cleanlab!**

“We used Cleanlab to quickly validate one of our classifier models’ predictions for a dataset. This is typically a very time-consuming task since we would have to check thousands of examples by hand. However, since Cleanlab helped us identify the data points that were most likely to have label errors, we only had to inspect an eighth of our dataset to see that our model was problematic. We later realized that this was due to a post-processing error in the dataset — something that would otherwise have taken a much longer time to notice.” — Seah Bei Ying, Data Analyst, The Stakeholder Company