MLflow is an open-source platform designed to manage the end-to-end machine learning lifecycle. It provides a comprehensive suite of tools for experiment tracking, model versioning, and deployment.
By integrating with popular ML frameworks, MLflow simplifies the workflow for data scientists and engineers.With its modular design, MLflow includes four key components: Tracking, Projects, Models, and Model Registry.
These components enable users to log experiments, package code into reusable projects, manage and deploy models, and maintain a centralized model repository. Its flexibility and scalability make it an essential tool for ML practitioners.
