My experience with Comet has been very positive, but there are a few areas where it could be improved. One area is the learning curve for new users. Some of the more advanced features can feel overwhelming at first, especially for students who are new to machine learning experiment tracking. More beginner-friendly tutorials and guided onboarding would help. I would also like to see more customization options for dashboards and visualizations, making it easier to create views tailored to specific projects. Another improvement would be deeper integration with commonly used collaboration tools, which would streamline project documentation and team workflows. There are a few additional areas where Comet could improve. From a performance perspective, I occasionally notice that dashboards with a large number of experiments can take longer to load or navigate. Regarding documentation, while the available resources are helpful, I would appreciate more beginner-focused examples, step-by-step tutorials, and real-world use cases. For support, my experience has generally been good, but having more community resources, discussion forums, webinars, or educational content specifically aimed at students and researchers would be valuable.
