Charmed MLflow Documentation¶
Charmed MLflow is a platform for managing the end-to-end machine learning lifecycle.
It provides tools for tracking experiments, packaging code into reproducible runs, and sharing and deploying models. It integrates with popular machine learning frameworks.
It addresses a number of common machine learning challenges: collaboration, reproducibility, maintenance, organisation and scaling.
It’s ideal for data scientists, ML engineers, hobbyists and teams looking to optimise their ML workflows with charms.
In this documentation¶
Start here: a hands-on introduction to Charmed MLflow for newcomers
Step-by-step guides covering key operations and common tasks in Charmed MLflow
Technical information - specifications, APIs, architecture of Charmed MLflow
Discussion and clarification of key Charmed MLflow concepts and features
Project and community¶
Charmed MLflow is an open-source project that values its community. We warmly welcome contributions, suggestions, fixes, and constructive feedback from everyone.