114 Open source projects that are alternatives of or similar to Xgboost Predictor Java

Kaggle Kernels (Python, R, Jupyter Notebooks)

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

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

[ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples

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

2017第一届腾讯社交广告高校算法大赛Rank28_code

stratigraphic machine-learning - active work moved to Predictatops

Original implementation of Calibrated Boosting-Forest

An End to End Customer Churn Prediction solution using AWS services.

Trading Algorithm by XGBoost

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

AI100文本分类竞赛代码。从传统机器学习到深度学习方法的测试

Use advanced feature engineering strategies and select best features from your data set with a single line of code.

Rust bindings for XGBoost.

An extension of XGBoost to probabilistic forecasting

It's a github repo star predictor that tries to predict the stars of any github repository having greater than 100 stars.

Kaggle getting started competition examples

Animated Visualizations of Popular Machine Learning Algorithms

住房月租金预测大数据赛TOP1

Material of the Kaggle Berlin meetup group!

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

⏱ Benchmarks of machine learning inference for Go

关注AI模型上线、模型部署

Building Decision Trees From Scratch In Python

Attempt to predict future stock prices based on Google Trends data.

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

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

[Done] Master version: developed the stacked regression (score 0.11, top 5%) based on (xgboost, sklearn). Branch v1.0: developed linear regression (score 0.45) based on Tensorflow

Scalable machine 🤖 learning for time series forecasting.

Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.

Data Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala.

Bayesian Optimization and Grid Search for xgboost/lightgbm

Automatic machine learning for tabular data. ⚡🔥⚡

Machine learning models for time series analysis

Earthquake Prediction Challenge with LightGBM and XGBoost

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

📒 Experiment tracking tool and model registry

a solution for competition of kaggle `Human or Robot`

Convert XGBoost's DMatrix format to np.array

Secure collaborative training and inference for XGBoost.

🌳 Stacked Gradient Boosting Machines

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

This is the Docker container based on open source framework XGBoost (https://xgboost.readthedocs.io/en/latest/) to allow customers use their own XGBoost scripts in SageMaker.

Machine Learning University: Decision Trees and Ensemble Methods

Data and Code to reproduce results for my talk at Paris: R in Insurance 2017 Conference

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

《统计学习方法》与常见机器学习模型(GBDT/XGBoost/lightGBM/FM/FFM)的原理讲解与python和类库实现

Serverless Inferencing on Kubernetes

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

Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/

Implemented an A/B Testing solution with the help of machine learning

Machine Learning Operator & Controller for Kubernetes

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

A data-driven tool to identify the best candidates for a marketing campaign and optimize it.

https://events.kaspersky.com/hackathon/

Tiny Gradient Boosting Tree

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

A full pipeline AutoML tool for tabular data

A repository for some of the code I used in kaggle data science & machine learning tasks.

Quora Kaggle Competition : Natural Language Processing using word2vec embeddings, scikit-learn and xgboost for training