Summary
This blog post from Netflix discusses how they democratized machine learning within their organization by building the Model Lifecycle Graph (MLG). This system connects disparate ML metadata across various business domains to enhance collaboration and efficiency among machine learning practitioners. The MLG aims to overcome fragmentation by providing a unified infrastructure that allows teams to explore relationships between models, features, datasets, and A/B tests, ultimately facilitating deeper insights and streamlined workflows. Key challenges in maintaining the MLG include tool integration, metadata quality assurance, and advanced relationship inference.