How Sainsbury's is Bridging the Gap from Model Creation to Production
Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. Join Rico, a Machine Learning Engineer from Sainsburys, as he talks through how Metaflow provides a unified API to the infrastructure stack that is required to execute data science projects, from prototype to production.
Key Takeaways: • Metaflow allows data science teams to take a workflow from creation to the cloud to production within hours instead of days or even weeks. • It uses an internal DAG (directed acyclic graph) structure to orchestrate workflows; these can be turned into AWS Step Functions with just one command. • It solves a big problem for companies who are looking to bridge the gap between data science and engineering.
Enterprising, extroverted Data Scientist with a passion for Artificial Intelligence (AI)/Machine Learning (ML) and a unique ability to easily forge relationships with colleagues, customers, and other business partners. I help data science teams deliver value and ship models with measurable results for the business. At Sainsbury's Tech, I am responsible for building Data Science and Machine Learning models and engineering them to run in production using AWS.