Even though H2O.ai provides the best model, there could be improvements in certain areas. For instance, when you want to work with fusion models, H2O.ai doesn't provide that kind of information. Currently, it provides individual models as outcomes. If it could offer combinations of models, such as suggesting using XGBoost along with SVM for wonderful results, that fusion model concept would be a good option for developers. I hope the fusion model concept will be implemented soon in H2O.ai. Regarding documentation, I faced challenges as I didn't see much information from a documentation perspective. When I was trying to learn how to train and test H2O.ai, there was limited documentation available. If they could improve in that area, it would be really beneficial.
