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Growth reflects Iterative’s mission to streamline the workflow of data scientists and machine learning engineers
Iterativethe MLOps company dedicated to streamlining the workflow of data scientists and machine learning (ML) engineers, reached a number of important milestones in 2021. Highlights include introduce the Data Version Control (DVC) and Continuous Machine Learning (CML) open source projects followed by the addition of Experiment Versioning in DVC.
Iterative was founded in 2018 and in less than three years, its tools have had more than 8 million sessions and are rapidly growing, with more than 12,000 stars on GitHub between CML and DVC. DVC users grew by almost 95% in 2021 with over 3000 monthly users. Iterative now has more than 300 contributors across the different tools.
“Iterative’s tools have been critical in helping our machine learning team grow and unlock their productivity,” said Benjamin Jones, head of ML at DeGould. “Before using DVC, we struggled to share data and pipelines were steps written in READMEs. Since adopting DVC and CML, we’ve been able to easily collaborate and share data and experiments across team members to …
Full story available on Benzinga.com
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