ElandPython Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
Eli5A library for debugging/inspecting machine learning classifiers and explaining their predictions
MmlsparkSimple and Distributed Machine Learning
Unbiased lambdamartCode for WWW'19 "Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm", which is based on LightGBM
Gbm PerfPerformance of various open source GBM implementations
MarsMars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
LightgbmA fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
ForecastingTime Series Forecasting Best Practices & Examples
M2cgenTransform 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
RecotourA tour through recommendation algorithms in python [IN PROGRESS]
NyokaNyoka is a Python library to export ML/DL models into PMML (PMML 4.4.1 Standard).
Auto ml[UNMAINTAINED] Automated machine learning for analytics & production
Lightgbm With Focal LossAn implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems
Learning to rank利用lightgbm做(learning to rank)排序学习,包括数据处理、模型训练、模型决策可视化、模型可解释性以及预测等。
MlboxMLBox is a powerful Automated Machine Learning python library.
Mljar SupervisedAutomated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀
AutodlAutomated Deep Learning without ANY human intervention. 1'st Solution for AutoDL [email protected]
Hyperparameter hunterEasy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
OpenscoringREST web service for the true real-time scoring (<1 ms) of Scikit-Learn, R and Apache Spark models
Leavespure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks
DmtkMicrosoft Distributed Machine Learning Toolkit
HyperGBMA full pipeline AutoML tool for tabular data
HumanOrRobota solution for competition of kaggle `Human or Robot`
Arch-Data-ScienceArchlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision
arfsAll Relevant Feature Selection
lleavesCompiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.
Kaggle-Competition-SberbankTop 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market
kaggle-plasticcSolution to Kaggle's PLAsTiCC Astronomical Classification Competition
autogbt-altAn experimental Python package that reimplements AutoGBT using LightGBM and Optuna.
recsys2019The complete code and notebooks used for the ACM Recommender Systems Challenge 2019
SynapseMLSimple and Distributed Machine Learning
Apartment-Interest-PredictionPredict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.
mltbMachine Learning Tool Box
LightGBM.jlLightGBM.jl provides a high-performance Julia interface for Microsoft's LightGBM.
lightgbmExplainerAn R package that makes lightgbm models fully interpretable (take reference from https://github.com/AppliedDataSciencePartners/xgboostExplainer)
ml-pipelineUsing Kafka-Python to illustrate a ML production pipeline
datascienvdatascienv 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
mlforecastScalable machine 🤖 learning for time series forecasting.
AutoTabularAutomatic machine learning for tabular data. ⚡🔥⚡
KaggleKaggle Kernels (Python, R, Jupyter Notebooks)