{"id":19431729,"url":"https://github.com/bioinformatist/cml","last_synced_at":"2025-10-04T01:47:44.453Z","repository":{"id":179327631,"uuid":"661762461","full_name":"bioinformatist/cml","owner":"bioinformatist","description":"A Framework for Production-Ready Continuous Machine 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align=\"center\"\u003e\n  \u003ch1\u003eCML\u003c/h1\u003e\n  \u003cem\u003e\"Domain generalization is dead, Continuous Machine Learning lives forever.\" —— an iKun\u003c/em\u003e\n\u003ctable\u003e\n    \u003ctbody\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\u003cimg src=\"assets/cml.png\" width=\"188px\"/\u003e\u003c/td\u003e\n            \u003ctd\u003e\n                \u003cp\u003e\u003cstrong\u003eCML is a framework for production-ready continuous machine learning in pure Rust.\u003c/strong\u003e\u003c/p\u003e\n                \u003ca href='https://github.com/bioinformatist/cml/actions/workflows/coveralls.yml'\u003e\n                    \u003cimg src='https://github.com/bioinformatist/cml/actions/workflows/coveralls.yml/badge.svg' alt='Test Status' /\u003e\n                \u003c/a\u003e\n                \u003ca href='https://coveralls.io/github/bioinformatist/cml'\u003e\n                    \u003cimg src='https://coveralls.io/repos/github/bioinformatist/cml/badge.svg' alt='Coverage Status' /\u003e\n                \u003c/a\u003e\n            \u003c/td\u003e\n        \u003c/tr\u003e\n    \u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\n## Motivation\n\nDomain-specific problem are widely prevalent in real-world scenarios.\n\n\u003cimg src=\"assets/domain-specific.png\" width=\"518px\"/\u003e\n\nTo address this problem:\n\n\u003ctable\u003e\n    \u003cthead\u003e\n        \u003ctr\u003e\n            \u003cth\u003eTraditional method\u003c/th\u003e\n            \u003cth\u003eCML method\u003c/th\u003e\n        \u003c/tr\u003e\n    \u003c/thead\u003e\n    \u003ctbody\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\n                \u003cul\u003e\n                    \u003cli\u003eIncreasing the amount of training data\u003c/li\u003e\n                    \u003cli\u003eOptimizing model architecture\u003c/li\u003e\n                    \u003cli\u003eApplying diverse data augmentation techniques\u003c/li\u003e\n                \u003c/ul\u003e\n            \u003c/td\u003e\n            \u003ctd\u003eCombining \u003cstrong\u003eC\u003c/strong\u003eontinuous Integration\u003c/br\u003ewith \u003cstrong\u003eM\u003c/strong\u003eachine \u003cstrong\u003eLearning\u003c/strong\u003e\u003c/td\u003e\n        \u003c/tr\u003e\n        \u003ctr\u003e\n            \u003ctd\u003e\u003cimg src=\"assets/traditional.png\" width=\"688px\"/\u003e\u003c/td\u003e\n            \u003ctd\u003e\u003cimg src=\"assets/new.png\" width=\"388px\"/\u003e\u003c/td\u003e\n        \u003c/tr\u003e\n    \u003c/tbody\u003e\n\u003c/table\u003e\n\n## How does it work?\n\nSee our [architecture document](ARCHITECTURE.md).\n\n## Contributing\n\nThere is currently no code of conduct document available. However, we highly recommend that you read our [architecture document](ARCHITECTURE.md) first and foremost.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbioinformatist%2Fcml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbioinformatist%2Fcml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbioinformatist%2Fcml/lists"}