https://github.com/bioinformatist/cml

A Framework for Production-Ready Continuous Machine Learning
https://github.com/bioinformatist/cml

artificial-intelligence continuous-machine-learning deep-learning machine-learning mlops

Last synced: 6 days ago
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A Framework for Production-Ready Continuous Machine Learning

• Host: GitHub
• URL: https://github.com/bioinformatist/cml
• Owner: bioinformatist
• License: bsd-3-clause
• Created: 2023-07-03T15:29:46.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-01-21T11:54:31.000Z (10 months ago)
• Last Synced: 2024-01-21T12:39:27.190Z (10 months ago)
• Topics: artificial-intelligence, continuous-machine-learning, deep-learning, machine-learning, mlops
• Language: Rust
• Homepage:
• Size: 321 KB
• Stars: 5
• Watchers: 3
• Forks: 2
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        


  
CML

  "Domain generalization is dead, Continuous Machine Learning lives forever." —— an iKun


    

        

            

            

                
CML is a framework for production-ready continuous machine learning in pure Rust.

                

                    

                

                

                    

                

            

        

    




## Motivation

Domain-specific problem are widely prevalent in real-world scenarios.



To address this problem:

    

        

            Traditional method

            CML method

        

    

    

        

            

                


                    
Increasing the amount of training data

                    
Optimizing model architecture

                    
Applying diverse data augmentation techniques

                

            

            Combining Continuous Integrationwith Machine Learning

        

        

            

            

        

    


## How does it work?

See our [architecture document](ARCHITECTURE.md).

## Contributing

There is currently no code of conduct document available. However, we highly recommend that you read our [architecture document](ARCHITECTURE.md) first and foremost.