xgboost
There are 3738 repositories under xgboost topic.
dmlc/xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
MingchaoZhu/DeepLearning
Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
kserve/kserve
Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes
alibaba/Alink
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
mljar/mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
parrt/dtreeviz
A python library for decision tree visualization and model interpretation.
BayesWitnesses/m2cgen
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
TeamHG-Memex/eli5
A library for debugging/inspecting machine learning classifiers and explaining their predictions
mars-project/mars
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
jolibrain/deepdetect
Deep Learning API and Server in C++14 support for PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
benedekrozemberczki/awesome-decision-tree-papers
A collection of research papers on decision, classification and regression trees with implementations.
kubeflow/trainer
Distributed AI Model Training and Fine-Tuning on Kubernetes
szilard/benchm-ml
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
minimaxir/automl-gs
Provide an input CSV and a target field to predict, generate a model + code to run it.
AutoViML/AutoViz
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
ClimbsRocks/auto_ml
[UNMAINTAINED] Automated machine learning for analytics & production
AxeldeRomblay/MLBox
MLBox is a powerful Automated Machine Learning python library.
skforecast/skforecast
Time series forecasting with machine learning models
xorbitsai/xorbits
Scalable Python DS & ML, in an API compatible & lightning fast way.
Nixtla/mlforecast
Scalable machine 🤖 learning for time series forecasting.
benedekrozemberczki/awesome-gradient-boosting-papers
A curated list of gradient boosting research papers with implementations.
SeldonIO/MLServer
An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
the-black-knight-01/Data-Science-Competitions
Goal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).
HunterMcGushion/hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
AutoViML/featurewiz
Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.
StatMixedML/XGBoostLSS
An extension of XGBoost to probabilistic modelling
HuangCongQing/AI_competitions
AI比赛相关信息汇总
neptune-ai/neptune-client
📘 The experiment tracker for foundation model training
openscoring/openscoring
REST web service for the true real-time scoring (<1 ms) of Scikit-Learn, R and Apache Spark models
cerlymarco/shap-hypetune
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
hczheng/Rong360
用户贷款风险预测
linkedin/FastTreeSHAP
Fast SHAP value computation for interpreting tree-based models
AutoViML/Auto_ViML
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
SimonBlanke/Hyperactive
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
mljar/supertree
Visualize decision trees in Python
h2oai/mli-resources
H2O.ai Machine Learning Interpretability Resources