QuantumBlack open sources its data analytics framework

A new open source framework that aims to make building machine learning pipelines easier for data scientists was released today by QuantumBlack, the data analytics outfit snapped up by McKinsey in 2015 and that has its roots in data work for Formula 1 racing teams. The firm hopes that the fully open source development workflow, called Kedro, will become an industry standard for production-ready code in machine learning and data science. Speaking with Computerworld UK, Michele Battellli, global head of engineering and product at QuantumBlack, explains: "Kedro is a library of code that can be used to create data and machine learning pipelines - basically the building blocks of what we do in an analytics or machine learning project. "It changes the way data scientists and engineers collaborate and work together with large workflows and data sets, so that the output of their work is something that will be production-ready. In essence, it allows teams to collaborate more easily because ...