Data Sci & Algos

Innovating on Software Development

We have seen a rapid explosion in tools in the machine learning and data ecosystem. These tools cover an expansive surface area, which includes orchestration, observability, experiment tracking, data quality, and more. Despite the proliferation of tools, one activity core to everyone’s workflow has been largely ignored: writing and distributing software. In this talk, Hamel will discuss innovative approaches and tools for software development, their history, and future directions. Hamel will discuss the historical threads upon which these new approaches are built, and discuss nbev, a popular open-source project that implements many of these ideas. Finally, Hamel will share learnings from building nbdev, along with challenges and future directions.