Tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours.
DataRobot automates processes, cutting costs and reducing project timelines from months to weeks. It excels in feature engineering, simplifying MLOps, and boosting productivity. However, it faces issues with performance, repository integration, and high pricing. Users find models resemble a black box and seek better integration for Python, R code, and proprietary algorithms. Improvements are needed for generative AI and large language models handling.
