Deploy and Monitor ML Pipelines with Open Source and Free Applications

Deploy and Monitor ML Pipelines with Open Source and Free Applications

Explore the deployment of machine learning pipelines using open-source applications and free-tier tools in this 45-minute workshop. Learn to automate data refresh processes and generate regular forecasts using GitHub Actions and Docker, demonstrated through the US hourly electricity demand data from the EIA API. Discover how to implement open-source tools like MLflow and YData Profiling for monitoring data health and model performance. Set up a monitoring dashboard using Quarto doc and deploy it on GitHub Pages, gaining practical insights into efficient ML pipeline management and deployment strategies.