Recently, Plat.AI introduced new possibilities in the AutoML codeless modeling platform. In addition to linear regression models, AutoML users can now train XGBoost tree-based models and neural network models.
This marks a significant milestone. Through our Automated Tree-Based and Neural Network Model Fitting, we can provide more robust and efficient analytical tools. We also have enhanced Targeting Capabilities, allowing users to build models for both classification and regression targets, expanding the scope of our solutions.
This array of configuration options is wide enough to meet the needs of seasoned data scientists without being too complex for beginner analysts.
Aside from the above, we are making continuous improvements and releasing more features in the AutoML platform.
We value your feedback, so dive into the upgraded experience and let us know what you think!
