CatBoost is an algorithm for gradient boosting on decision trees.
It is used for search, recommendation systems, personal assistant, self-driving cars, weather prediction, etc.
Most powerful version of gradient boosting.
It is a gradient boosting based algorithm, which provides not only amazing results, you know, amazing accuracies, or even regression score. But also it has a very special feature, which will absolutely love, which is self tuning.
Self tuning means that the CatBoost model doesn’t require to be tuned. In other words, it will tune itself in order to find the best parameters that will lead to the best score of performance. You know, the best accuracy or the best R2 (R-squared) for regression.