Awesome C++
Section: Machine Learning · A fast, scalable, high performance Gradient Boosting on Decision Trees library. [Apache2]
FreshScore 94
Entry
CatBoost
Appears in 10 awesome lists
General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.
Open github.comcatboost/catboost
Found in these lists
Awesome Data Analysis
Section: Tools · High-performance gradient boosting on decision trees with categorical features support.
FreshScore 80
AWESOME DATA SCIENCE
Section: General Machine Learning Packages
FreshScore 92
Awesome Machine Learning
Section: C++ · General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.
FreshScore 93
Awesome Open Source AI
Section: 1. Core Frameworks & Libraries · Gradient boosting that handles categorical features natively with great out-of-the-box performance.
FreshScore 89
Awesome Python
Section: Machine Learning · A fast, scalable, high performance gradient boosting on decision trees library.
FreshScore 94
Awesome Python Data Science
Section: Gradient Boosting · An open-source gradient boosting on decision trees library.
ActiveScore 71
awesome-c
Section: Machine Learning Frameworks · A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
FreshScore 80
awesome-cpp
Section: Machine Learning Frameworks · A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
FreshScore 79
awesome-python
Section: Machine Learning Frameworks · A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
FreshScore 81
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