68 Open source projects that are alternatives of or similar to Lightgbm_predict4j

Kaggle Kernels (Python, R, Jupyter Notebooks)

Building Decision Trees From Scratch In Python

Bayesian Optimization and Grid Search for xgboost/lightgbm

Using Kafka-Python to illustrate a ML production pipeline

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

Archlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision

🏆 Kaggle 8th place solution

Open solution to the Mapping Challenge 🌎

Simple and Distributed Machine Learning

An experimental Python package that reimplements AutoGBT using LightGBM and Optuna.

LightGBM.jl provides a high-performance Julia interface for Microsoft's LightGBM.

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

基于移动网络通讯行为的风险用户识别 (15th/624)

Scalable machine 🤖 learning for time series forecasting.

AI比赛相关信息汇总

📒 Experiment tracking tool and model registry

关注AI模型上线、模型部署

A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms

文本分类基准测试

Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch

Top 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks

5th place solution for Kaggle competition Favorita Grocery Sales Forecasting

Machine Learning University: Decision Trees and Ensemble Methods

Machine Learning Tool Box

A collection of research papers on decision, classification and regression trees with implementations.

A full pipeline AutoML tool for tabular data

An R package that makes lightgbm models fully interpretable (take reference from https://github.com/AppliedDataSciencePartners/xgboostExplainer)

REST web service for the true real-time scoring (<1 ms) of Scikit-Learn, R and Apache Spark models

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

a solution for competition of kaggle `Human or Robot`

Automatic machine learning for tabular data. ⚡🔥⚡

Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL [email protected]

Earthquake Prediction Challenge with LightGBM and XGBoost

All Relevant Feature Selection

🌳 Stacked Gradient Boosting Machines

Open solution to the Home Credit Default Risk challenge 🏡

Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).

Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.

Show how to perform fast retraining with LightGBM in different business cases

Open solution to the Santander Value Prediction Challenge 🐠

머신러닝/딥러닝(PyTorch, TensorFlow) 전용 도커입니다. 한글 폰트, 한글 자연어처리 패키지(konlpy), 형태소 분석기, Timezone 등의 설정 등을 추가 하였습니다.

2017第一届腾讯社交广告高校算法大赛Rank28_code

A library for debugging/inspecting machine learning classifiers and explaining their predictions

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

Code for WWW'19 "Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm", which is based on LightGBM

Solution to Kaggle's PLAsTiCC Astronomical Classification Competition

Performance of various open source GBM implementations

A curated list of gradient boosting research papers with implementations.

A 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.

The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

Time Series Forecasting Best Practices & Examples

Microsoft Distributed Machine Learning Toolkit

Simple and Distributed Machine Learning

Precompiled packages for AWS Lambda

Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

住房月租金预测大数据赛TOP1

Predict people interest in renting specific NYC apartments. The challenge combines structured data, geolocalization, time data, free text and images.