Design an ML experiment tracking and analysis platform.

Focus on the core functionalities that an ML experiment tracking and analysis platform should provide. Consider how users will log experiments, track metrics, and visualize results. Discuss the importance of version control for datasets and models, as well as the need for collaboration features among data scientists. Address scalability and integration with existing ML tools and frameworks. Finally, think about user experience—how will you ensure that the platform is intuitive for both technical and non-technical users?