Follow along as data scientists adopt DevSecOps practices and enjoy the benefits of automation, repeatable workflows, standardization, and automatic provisioning of infrastructure.

GitLab is a complete DevOps platform delivered as a single application, offering integrated tools for version control, CI/CD, issue tracking, and collaboration. Users can learn about GitLab's DevOps workflow, CI/CD pipelines, and collaboration features to streamline their software development lifecycle and accelerate delivery.

GitLab

Building predictive models requires experimentation and iterations. GitLab's Data Science team uses the DevSecOps platform to enhance reproducibility, automate ML model training, and leverage ML experiment tracking.

Building GitLab with GitLab: Why there is no MLOPs without DevSecOps

How to build the data science image using GitLab CI/CD

Automate training and re-training of ML models with GPU-enabled CI/CD