iterative/cml

Health v2 · maintenance only

Adoption not part of the score

4187 stars · 344 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

CML (Continuous Machine Learning) is an open-source CLI tool that brings CI/CD practices to machine learning projects on GitHub, GitLab, and Bitbucket. It automates model training and evaluation, provisions cloud or self-hosted runners, and posts visual reports with metrics and plots on every pull request.

Use cases

• add ci/cd to machine learning projects
• auto-generate ml experiment reports on pull requests
• train and evaluate models in github actions or gitlab ci
• compare ml experiments across project history
• provision self-hosted or cloud runners for ml training
• monitor changing datasets in ci pipelines
• build an ml platform without extra services

When to choose

• you want MLOps automation using only your existing Git hosting platform
• you need automatic metrics and plot reports in pull requests
• you use DVC and want data and models in your CI pipeline
• you want to avoid running a separate ML platform service

When to avoid

• you need a full managed ML platform with UI-based experiment tracking
• your project is not hosted on GitHub, GitLab, or Bitbucket
• you don't use CI/CD workflows for your ML development

Facets

cli-tool · maturity active

ci-cd cli workflow-automation machine-learning data-visualization machine-learning data-science developer-tools cli cloud self-hosted mlops github-actions gitlab-ci bitbucket-pipelines dvc continuous-integration continuous-delivery experiment-tracking iterative-ai reporting devops automation nodejs docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="iterative/cml")