Summary
We have just completed the journey to perform model evaluation in Comet!
Throughout this chapter, we described some general concepts regarding model evaluation, as well as the main techniques to evaluate regression, classification, and clustering. We also illustrated the importance of model evaluation in a data science project; model evaluation permits us to define some metrics to choose the best model for production.
In the third part of the chapter, you learned which features Comet provides to perform model evaluation and how you can use them through a practical example. We deepened the concepts of logs and reports, which you already knew about, and illustrated two new concepts, the Comet Dashboard and the Model Registry.
Throughout this chapter, you learned how easy it is to use Comet to run model evaluation, as Comet provides very intuitive features that can be combined to build fantastic reports, as well as how to keep track of the best model for production...
