Continuous Machine Learning (CML)

Topics covered.

• CML
• DVC
• Github Actions.

Automate, customize, and execute your software development workflows right in your repository with GitHub Actions. You can discover, create, and share actions to perform any job you'd like, including CI/CD, and combine actions in a completely customized workflow.

For more information:

• https://docs.github.com/en/actions/quickstart
• https://docs.github.com/en/actions/learn-github-actions

Open-source Version Control System for Machine Learning Projects

DVC tracks ML models and data sets. DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code.

For more information:

• https://dvc.org/features

Continuous Machine Learning (CML) is an open-source CLI tool for implementing continuous integration & delivery (CI/CD) with a focus on MLOps. Use it to automate development workflows — including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets.

CML can help train and evaluate models — and then generate a visual report with results and metrics — automatically on every pull request.

For more information:

• https://github.com/iterative/cml
• https://github.com/iterative/example_cml