Uncovering Community and Project Insights Through Data-Driven Methods

Explore data-driven methods for assessing and tracking open source project health in this 24-minute conference talk. Learn how to extract valuable insights from GitHub repositories, including velocity, blockers, and community health metrics. Discover techniques for creating open source data science workflows to collect, analyze, and visualize key metrics on dashboards. Gain knowledge on building and deploying machine learning models to enhance project development processes. Understand how to leverage an open source community cloud environment for data scientists to solve challenges without infrastructure setup. Master the use of ML tools to derive key metrics from GitHub repositories and utilize open source tools for creating reproducible notebooks, models as services, automated pipelines, and dashboards.