CatBoost
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Explore more → **CatBoost**
What is CatBoost?
CatBoost is a high-performance open-source gradient boosting library developed by Yandex. It is designed to handle categorical features effectively, often outperforming other algorithms in datasets with many categorical variables. It is commonly used for classification, regression, ranking, and other machine learning tasks.
What other technologies are related to CatBoost?
CatBoost Competitor Technologies
LightGBM
LightGBM is a gradient boosting framework that competes with CatBoost in terms of speed and accuracy.
XGBoost
XGBoost is a popular gradient boosting library that, like CatBoost, is used for classification and regression tasks, serving as a direct competitor.
Number of organizations that mention technology
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CatBoost Complementary Technologies
scikit-learn
Scikit-learn provides tools for model selection, preprocessing, and evaluation that can be used alongside CatBoost.
Pandas
Pandas is a data manipulation library that is often used for preparing data to be used with CatBoost.
Seaborn
Seaborn is a data visualization library used for visualizing the results of CatBoost models and understanding the data.
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Which job functions commonly mention CatBoost?
Machine Learning
0.2% of all Machine Learning jobs mention CatBoost
View 212
jobs on Sumble
MLOps Engineer
0.1% of all MLOps Engineer jobs mention CatBoost
View 12
jobs on Sumble
Data Scientist
0.1% of all Data Scientist jobs mention CatBoost
View 331
jobs on Sumble
Applied Scientist
0.1% of all Applied Scientist jobs mention CatBoost
View 12
jobs on Sumble
AI Engineer
32 AI Engineer jobs mention CatBoost
View 32
jobs on Sumble
Which organizations are mentioning CatBoost?
Johnson & Johnson
Health Care and Social Assistance
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