241 Open source projects that are alternatives of or similar to xgboost-lightgbm-hyperparameter-tuning

Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.

Learnable Embedding Space for Efficient Neural Architecture Compression

Hyperparameter optimization package of the mlr3 ecosystem

Material of the Kaggle Berlin meetup group!

Using Kafka-Python to illustrate a ML production pipeline

🏆 Kaggle 8th place solution

Kaggle getting started competition examples

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

A scikit-learn compatible implementation of hyperband

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

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

Streamlined Estimation for Static, Dynamic and Stochastic Treatment Regimes in Longitudinal Data

Simple and Distributed Machine Learning

Distribution transparent Machine Learning experiments on Apache Spark

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

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

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

《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

Secure collaborative training and inference for XGBoost.

A Python package for approximate Bayesian inference and optimization using Gaussian processes

Showcase for using H2O and R for churn prediction (inspired by ZhouFang928 examples)

⏱ Benchmarks of machine learning inference for Go

PHYSBO -- optimization tools for PHYsics based on Bayesian Optimization

pyrff: Python implementation of random fourier feature approximations for gaussian processes

Machine learning toolkits with Python

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

A library for creating and curating reproducible pipelines for scientific and industrial machine learning

Fitness landscape exploration sandbox for biological sequence design.

Serverless Inferencing on Kubernetes

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

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

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

Advanced High Performance Data Science Toolbox for R by Laurae

Trading Algorithm by XGBoost

Bayesian Optimization algorithms with various recent improvements

Deep Learning API and Server in C++14 support for Caffe, Caffe2, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE

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.

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。

Rust bindings for XGBoost.

Stacked Generalization (Ensemble Learning)

A fast xgboost feature selection algorithm

This repository focuses on training semantic segmentation models to predict the presence of floodwater for disaster prevention. Models were trained using SageMaker and Colab.

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

Using Bayesian Optimization to optimize hyper parameter in Keras-made neural network model.

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.).

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

A general-purpose pythonic genetic algorithm.

Provide an input CSV and a target field to predict, generate a model + code to run it.

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

Machine Learning Operator & Controller for Kubernetes

Mixed-Integer Parallel Efficient Global Optimization

A repository to keep track of all the code that I end up writing for my blog posts.

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

Solution to the Outbrain Click Prediction competition

Codebase for "AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization", ICML 2018.

Common library for serving TensorFlow, XGBoost and scikit-learn models in production.

Tutoriais de Python, Data Science, Machine Learning e Deep Learning - Sigmoidal

Solution to Kaggle's PLAsTiCC Astronomical Classification Competition

Diviner is a serverless machine learning and hyper parameter tuning platform