#Catboost
Showing 17 of 17 repositories tagged #catboost, ranked by stars
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.
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
A collection of research papers on decision, classification and regression trees with implementations.
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference.
Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢
Projects I completed as a part of Great Learning's PGP - Artificial Intelligence and Machine Learning
A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms
Automatic machine learning for tabular data. ⚡🔥⚡
Tennis AI to predict the winner in ATP matches with 3 different models and a web UI
datascienv is package that helps you to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries
:octocat: Detection and Prediction of Air quality Index :octocat:
Python Scripts and Jupyter Notebooks
Demo on the capability of Yandex CatBoost gradient boosting classifier on a fictitious IBM HR dataset obtained from Kaggle. Data exploration, cleaning, preprocessing and model tuning are performed on the dataset
🏠 A Data Science Project done to find the factors that most affect the price of an Airbnb listing.