Machine Learning Operations (MLOps) is a methodology that embraces automation to incrementally improve business outcomes for machine learning problems. Now more than ever, organizations are focused on creating processes that maximize developer efficiency and bolster product innovation. Using GitHub to teach machine learning operations (MLOps) provides four major benefits: reproducibility (via GitHub 代码空间), access to machine learning technology, AI coding assistance, and CI/CD capabilities. This video Guide shows how to utilize the features provided by GitHub and walks viewers through building GitHub Templates, creating a CI/CD workflow with GitHub 操作, and configuring GitHub 代码空间 environments with .devcontainer. Along the way, you’ll learn how automation and AI pair programming can help streamline these processes.
In this Guide, you will learn:
To setup and use GitHub 操作
To setup and use Github 代码空间 with templates for MLOps with GPU capability
To setup and use GitHub Copilot for AI pair programming
