CI/CD for ML Pipelines on Debian 13

CI/CD for ML Pipelines is an automated framework designed to streamline the development, testing, deployment, and monitoring of machine learning models. It provides a unified, collaborative environment that enables teams to build, validate, and deploy ML workflows efficiently, ensuring reproducibility, scalability, and faster delivery of AI solutions.

Features of CI/CD for ML Pipelines:

• Automated model training, testing, and deployment using CI/CD tools like Jenkins, GitHub Actions, or GitLab CI.
• Integration with ML frameworks and tools such as MLflow, DVC, TensorFlow, or PyTorch.
• Collaborative pipelines with version control for code, data, and models.
• Scalable orchestration using Docker, Kubernetes, or cloud-native services.
• Monitoring, logging, and workflow automation for continuous improvement of ML models.

To access the ML pipeline service or tracking UI (for example, MLflow, if configured on port 8080), open the following URL in your browser:

http://<your-server-ip>:8080

Disclaimer: CI/CD for ML pipelines requires proper setup and configuration of the underlying tools and infrastructure. Users are responsible for configuring pipelines, access controls, compute resources, and data security. While CI/CD simplifies ML workflow automation and deployment, proper governance and monitoring are essential for reliable and secure ML operations.