Crunching Your Data with CatBoost - the New Gradient Boosting Library
summary
Introduces CatBoost, an open-source gradient boosting library, and demonstrates its performance advantages over other GBDT implementations. Covers CatBoost’s accuracy, its fastest-in-class prediction (applier) algorithm, and its GPU training speed, with practical tutorial-style material on using the library.
AI-written summary · about
related talks
40mCatBoost: Fast Open-Source Gradient Boosting Library For GPU
38mCatBoost - the new generation of gradient boosting
01h 27mCatBoost - The New Generation of Gradient Boosting
01h 28mMastering gradient boosting with CatBoost
37mGradient Boosting for Data with Both Numerical and Text Features
18mCompetitive Analysis of the Top Gradient...
32mDeep Dive into scikit-learn's HistGradientBoosting Classifier..
42mHow am I going to deal with all of these cats
