Lydian Lee, ML Platform Tech Lead; Ryan Irwin, Engineering Manager
- Oct 21, 2020
Jupyter notebooks are a key tool that powers Yelp data. It allows us to do ad hoc development interactively and analyze data with visualization support. As a result, we rely on Jupyter to build models, create features, run Spark jobs for big data analysis, etc. Since notebooks play a crucial role in our business processes, it is really important for us to ensure the notebook output is reproducible. In this blog post, we’ll introduce our notebook archive and sharing service called Folium and its key integrations with our Jupyterhub that enable notebook reproducibility and improve ML engineering developer velocity. Folium...