MLflow: A platform for managing the machine learning lifecycle
O'Reilly Media - Data
JULY 17, 2018
An overview of the challenges MLflow tackles and a primer on how to get started. Although machine learning (ML) can produce fantastic results, using it in practice is complex. Beyond the usual challenges in software development, machine learning developers face new challenges, including experiment management (tracking which parameters, code, and data went into a result); reproducibility (running the same code and environment later); model deployment into production; and governance (auditing mode
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