Model Review: improve transparency, reproducibility, & info sharing with MLflow

We are excited to announce that we have a fun talk with Dr. Jes Ford. See the description below.

"Code Review is an integral part of software development, but many teams don’t have similar processes in place for the development and deployment of Machine Learning (ML) models. Jess will motivate the decision to create a Model Review process, starting from the principles of transparency, reproducibility, and knowledge sharing. MLflow is a useful Python package to help simplify and automate much of the tracking necessary to create detailed records of machine learning experiments. Much of this talk will be spent introducing this tool and demonstrating the core MLflow Tracking functionality. I’ll discuss how my team is currently running a Model Review process for any ML models that we push to production, and how we use MLflow to streamline this work and learn from each other." quote by Jes Ford.

Jes Ford is a sponsored snowboarder turned astrophysicist turned data scientist. She enjoys applying Python data science tools to a wide variety of problems, and teaching skills and best practices at local meetups. Jes has a Ph.D. in Physics from the University of British Columbia. She is currently an ML Engineer at Cash App (part of Block, formerly known as Square), and previously worked as a data scientist at Recursion and Backcountry.com.