I have utilized the AutoML feature in H2O.ai, which is one of the very powerful features where you don't need to worry about which algorithm is best for your model.
H2O.ai provides fast training and memory-efficient DataFrame manipulation, benefiting those transitioning from Spark. Integration with enterprise Java apps via POJO/MOJO enhances usability. AutoML facilitates model evaluation while driverless capability allows effective algorithm assessment. It supports Jupyter Notebooks and flexible model exploration, yet trails R and Pandas in data manipulation. Enhancements are needed in integration with systems like SageMaker, model management, multimodal support, and data source compatibility.
