Managing the Machine Learning Lifecycle with MLflow and R - Databricks

Managing the Machine Learning Lifecycle with MLflow and R

We provide an overview of the R interface for MLflow, an open source platform for managing end-to-end machine learning lifecycle. We demonstrate the three components of the framework—experiment tracking, project packaging, and model deployment—via concrete use cases.

Session hashtag: #SAISDS5



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About Kevin Kuo

Kevin is a software engineer at RStudio working on open source software for big data analytics and machine learning. Previously, he worked as a data scientist in a variety of companies, including Honeywell where he led machine learning projects using IIoT data, and KPMG where he worked with insurers to develop predictive models for pricing.