Topic: xgboost Goto Github
Some thing interesting about xgboost
Some thing interesting about xgboost
xgboost,关注AI模型上线、模型部署
User: aipredict
xgboost,Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
Organization: alibaba
xgboost,Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
User: autoviml
xgboost,Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
User: autoviml
xgboost,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.
User: autoviml
xgboost,Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker
Organization: aws-solutions-library-samples
xgboost,MLBox is a powerful Automated Machine Learning python library.
User: axelderomblay
Home Page: https://mlbox.readthedocs.io/en/latest/
xgboost,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
Organization: bayeswitnesses
xgboost,A collection of research papers on decision, classification and regression trees with implementations.
User: benedekrozemberczki
xgboost,A curated list of gradient boosting research papers with implementations.
User: benedekrozemberczki
xgboost,A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
User: cerlymarco
xgboost,[UNMAINTAINED] Automated machine learning for analytics & production
User: climbsrocks
Home Page: http://auto-ml.readthedocs.io
xgboost,A full pipeline AutoML tool for tabular data
Organization: datacanvasio
Home Page: https://hypergbm.readthedocs.io/
xgboost,pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks
User: dmitryikh
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
Organization: dmlc
Home Page: https://xgboost.readthedocs.io/en/stable/
xgboost,Real time eye tracking for embedded and mobile devices.
Organization: elucideye
xgboost,H2O.ai Machine Learning Interpretability Resources
Organization: h2oai
xgboost,AI比赛相关信息汇总
User: huangcongqing
xgboost,Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
User: huntermcgushion
xgboost,Time series forecasting with machine learning models
User: joaquinamatrodrigo
Home Page: https://skforecast.org
xgboost,Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE
Organization: jolibrain
Home Page: https://www.deepdetect.com/
xgboost,Pure Java implementation of XGBoost predictor for online prediction tasks.
User: komiya-atsushi
xgboost,Standardized Serverless ML Inference Platform on Kubernetes
Organization: kserve
Home Page: https://kserve.github.io/website/
xgboost,Distributed ML Training and Fine-Tuning on Kubernetes
Organization: kubeflow
Home Page: https://www.kubeflow.org/docs/components/training
xgboost,Fast SHAP value computation for interpreting tree-based models
Organization: linkedin
xgboost,Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
Organization: mars-project
Home Page: https://mars-project.readthedocs.io
xgboost,Machine learning models for time series analysis
User: maxim5
xgboost,Open solution to the Home Credit Default Risk challenge :house_with_garden:
Organization: minerva-ml
Home Page: https://www.kaggle.com/c/home-credit-default-risk
xgboost,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
User: mingchaozhu
xgboost,Provide an input CSV and a target field to predict, generate a model + code to run it.
User: minimaxir
xgboost,Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Organization: mljar
Home Page: https://mljar.com
xgboost,Visualize decision trees in Python
Organization: mljar
Home Page: https://mljar.com/supertree
xgboost,📘 The experiment tracker for foundation model training
Organization: neptune-ai
Home Page: https://neptune.ai
xgboost,Scalable machine 🤖 learning for time series forecasting.
Organization: nixtla
Home Page: https://nixtlaverse.nixtla.io/mlforecast
xgboost,REST web service for the true real-time scoring (<1 ms) of Scikit-Learn, R and Apache Spark models
Organization: openscoring
xgboost,A python library for decision tree visualization and model interpretation.
User: parrt
xgboost,Data Science Feature Engineering and Selection Tutorials
Organization: rasgointelligence
Home Page: https://www.rasgoml.com/
xgboost,An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
Organization: seldonio
Home Page: https://mlserver.readthedocs.io/en/latest/
xgboost,An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
User: simonblanke
Home Page: https://simonblanke.github.io/hyperactive-documentation
xgboost,An extension of XGBoost to probabilistic modelling
User: statmixedml
Home Page: https://statmixedml.github.io/XGBoostLSS/
xgboost,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.).
User: szilard
xgboost,A library for debugging/inspecting machine learning classifiers and explaining their predictions
Organization: teamhg-memex
Home Page: http://eli5.readthedocs.io
xgboost,Goal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).
User: the-black-knight-01
Home Page: https://interviewbubble.com
xgboost,Tiny Gradient Boosting Tree
User: wepe
xgboost,Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
Organization: western-oc2-lab
xgboost,Scalable Python DS & ML, in an API compatible & lightning fast way.
Organization: xorbitsai
Home Page: https://xorbits.readthedocs.io
xgboost,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
User: yzkang
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