GitHub topics: lightgbm
AxeldeRomblay/MLBox
MLBox is a powerful Automated Machine Learning python library.
Language: Python - Size: 50 MB - Last synced at: about 4 hours ago - Pushed at: over 1 year ago - Stars: 1,514 - Forks: 275
Ramtin-Karbaschi/SpaceshipTitanic_LGBMmodel
The machine learning model is trained utilizing the LightGBM algorithm based on the "Spaceship Titanic" dataset.
Language: Jupyter Notebook - Size: 1.23 MB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 1 - Forks: 0
mljar/mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Language: Python - Size: 9.44 MB - Last synced at: 3 days ago - Pushed at: 12 days ago - Stars: 3,144 - Forks: 419
Shengwei-Peng/PV-Power-Generation-Forecasting
A project focused on forecasting solar photovoltaic (PV) power generation using regional microclimate data. Implements machine learning models like CatBoost, LightGBM, and XGBoost for predictions, leveraging environmental features like temperature, humidity, wind speed, and solar radiation.
Language: Jupyter Notebook - Size: 28.6 MB - Last synced at: 2 days ago - Pushed at: about 2 months ago - Stars: 6 - Forks: 1
Sugaharaa/fraud-detection
Detecção de fraudes em transações financeiras
Language: Jupyter Notebook - Size: 1.47 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0
microsoft/LightGBM
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.
Language: C++ - Size: 22.5 MB - Last synced at: 3 days ago - Pushed at: 7 days ago - Stars: 17,150 - Forks: 3,875
BobLd/PdfPigMLNetBlockClassifier
Proof of concept of training a simple Region Classifier using PdfPig and ML.NET (LightGBM). The objective is to classify each text block in a pdf document page as either title, text, list, table and image.
Language: C# - Size: 1.1 MB - Last synced at: 1 day ago - Pushed at: about 5 years ago - Stars: 28 - Forks: 6
skforecast/skforecast
Time series forecasting with machine learning models
Language: Python - Size: 522 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 1,295 - Forks: 155
boubione/lightgbm-beaglebone
A minimal, stripped-down version of LightGBM optimized for edge devices running Debian 10, with no SciPy dependency. Perfect for embedded ARM systems like BeagleBone.
Language: Python - Size: 2.16 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0
microsoft/SynapseML
Simple and Distributed Machine Learning
Language: Scala - Size: 155 MB - Last synced at: 4 days ago - Pushed at: 7 days ago - Stars: 5,124 - Forks: 842
SeldonIO/MLServer
An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
Language: Python - Size: 57.4 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 795 - Forks: 193
xorbitsai/xorbits
Scalable Python DS & ML, in an API compatible & lightning fast way.
Language: Python - Size: 5.74 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 1,175 - Forks: 70
neptune-ai/neptune-client
📘 The experiment tracker for foundation model training
Language: Python - Size: 13 MB - Last synced at: 2 days ago - Pushed at: 9 days ago - Stars: 613 - Forks: 65
benedekrozemberczki/awesome-gradient-boosting-papers
A curated list of gradient boosting research papers with implementations.
Language: Python - Size: 1.48 MB - Last synced at: 1 day ago - Pushed at: about 1 year ago - Stars: 1,022 - Forks: 158
blei-lab/treeffuser
Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression on tabular data with tree-based diffusion models.
Language: Jupyter Notebook - Size: 80.3 MB - Last synced at: 3 days ago - Pushed at: 2 months ago - Stars: 43 - Forks: 4
sergio11/diabetes_prediction_ml
Predicting diabetes using machine learning models based on medical data 📊💉. The goal is to create an accurate and reliable diagnostic tool for early detection 🏥🤖.
Language: Jupyter Notebook - Size: 13.6 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 2 - Forks: 2
ankane/lightgbm-ruby
High performance gradient boosting for Ruby
Language: Ruby - Size: 3.75 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 81 - Forks: 4
ZahirAhmadChaudhry/Recommendation_Systems_Kaggle
This repository documents our comprehensive approach to building an effective recommendation system for predicting customer repurchases on Carrefour's eCommerce platform. Starting with simple statistical methods and progressing to advanced neural network architectures, we've explored multiple approaches to tackle this recommendation challenge.
Language: Python - Size: 18 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 0 - Forks: 0
elastic/eland
Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
Language: Python - Size: 20.9 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 668 - Forks: 107
DeepraMazumder/Hotel-Reviews-Sentiment-Analysis
A Machine Learning project to predict sentiments from hotel reviews for automated guest satisfaction analysis
Language: Jupyter Notebook - Size: 68.7 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 1 - Forks: 0
gtzjh/mymodels
Assemble an efficient interpretable machine learning workflow.
Language: Python - Size: 926 KB - Last synced at: 7 days ago - Pushed at: 8 days ago - Stars: 22 - Forks: 2
Nixtla/mlforecast
Scalable machine 🤖 learning for time series forecasting.
Language: Python - Size: 29.8 MB - Last synced at: 6 days ago - Pushed at: 26 days ago - Stars: 1,009 - Forks: 97
mars-project/mars
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
Language: Python - Size: 37 MB - Last synced at: about 18 hours ago - Pushed at: over 1 year ago - Stars: 2,722 - Forks: 327
deeko002/ctr-predictor-module
CTR prediction pipeline using SQL + LightGBM for real-time ad click forecasting
Language: Python - Size: 182 KB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 0 - Forks: 0
sanjurajveer/Fraud_detection
Model for categorising transactions into fraud or not
Language: Jupyter Notebook - Size: 6.34 MB - Last synced at: 8 days ago - Pushed at: 9 days ago - Stars: 0 - Forks: 0
benedekrozemberczki/awesome-decision-tree-papers
A collection of research papers on decision, classification and regression trees with implementations.
Language: Python - Size: 870 KB - Last synced at: 1 day ago - Pushed at: about 1 year ago - Stars: 2,398 - Forks: 342
samresume/EnergyPredictor-Kaggle
This project addresses the challenge of predicting baseline energy usage in buildings for performance-based financing. Participants estimate what energy a building *would have used* without retrofits, enabling fair billing and encouraging investment in energy efficiency.
Language: Jupyter Notebook - Size: 772 KB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 0 - Forks: 0
igopalakrishna/hotel-reservation-prediction
End-to-end MLOps project predicting hotel reservation cancellations using LightGBM, Flask, Docker, Jenkins, and Google Cloud Run.
Language: Jupyter Notebook - Size: 3.35 MB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 0 - Forks: 0
neZorinEgor/AdsAnalyzer
📰 Platform for analyzing the effectiveness of advertising campaigns by ml and data analys
Language: Jupyter Notebook - Size: 14.2 MB - Last synced at: 9 days ago - Pushed at: 10 days ago - Stars: 6 - Forks: 0
ryfeus/lambda-packs
Precompiled packages for AWS Lambda
Language: Python - Size: 1.76 GB - Last synced at: 1 day ago - Pushed at: over 1 year ago - Stars: 1,121 - Forks: 239
kyosek/NGBoost-experiments
Play around with NGBoost and compare with LightGBM and XGBoost
Language: Python - Size: 327 KB - Last synced at: 7 days ago - Pushed at: 10 months ago - Stars: 19 - Forks: 8
rishiraj/autolgbm
LightGBM + Optuna: Auto train LightGBM directly from CSV files, Auto tune them using Optuna, Auto serve best model using FastAPI. Inspired by Abhishek Thakur's AutoXGB.
Language: Python - Size: 1.06 MB - Last synced at: 2 days ago - Pushed at: about 3 years ago - Stars: 37 - Forks: 5
HunterMcGushion/hyperparameter_hunter
Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
Language: Python - Size: 7.27 MB - Last synced at: about 4 hours ago - Pushed at: over 4 years ago - Stars: 706 - Forks: 101
ZongXR/DCIC2025-RiverWaterPrediction
闽江，福建省最大独流入海河流，流域降水丰沛。在新型电力系统和新阶段水利高质量发展的环境下，如何缓解流域防汛压力，提升水资源利用率是水电企业高质量发展的重中之重。目前，基于传统水文学原理已实现未来9小时甲级精度的洪水预报，但存在遇见期与预见精度上仍有提升空间，因此，通过结合人工智能技术实现流域入库流量的精准预测，对保障水库安全调度、防洪及清洁能源稳定供应具有重大战略意义。
Language: Jupyter Notebook - Size: 216 MB - Last synced at: 12 days ago - Pushed at: 16 days ago - Stars: 1 - Forks: 0
association-rosia/crop-yield-estimate
Harness the power of machine learning to forecast rice and wheat crop yields per acre in India, aiming to empower smallholder farmers, combat poverty and malnutrition, utilizing data from Digital Green surveys to revolutionize agriculture and promote sustainable practices in the face of climate change for enhanced global food security.
Language: Python - Size: 22 MB - Last synced at: 13 days ago - Pushed at: about 1 year ago - Stars: 13 - Forks: 1
DataCanvasIO/HyperGBM
A full pipeline AutoML tool for tabular data
Language: Python - Size: 11 MB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 347 - Forks: 47
Arindam-GitH/FraudGuard-ML
A comprehensive machine learning project for detecting fraudulent payment transactions. Features 50,000 synthetic transactions, 4 ML models (Random Forest, XGBoost, LightGBM, CatBoost), 8 data visualizations, and SMOTE for handling class imbalance. Perfect for financial institutions and data scientists working on fraud detection systems.
Language: Python - Size: 10.7 KB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 1 - Forks: 0
deenayy/Algorithmic-Trading-Bot
The-project-aims-to-evaluate-the-predictive-performance-of-different-machine-learning-(ML)-algorithms-for-Bitcoin-trading.-The-proposed-trading-strategy-integrates-key-technical-indicators,-including-the-Relative-Strength-Index-(RSI),-Simple-and-Exponential-Moving-Averages,-and-the-Moving-Average-Convergence-Divergence-(MACD).
Language: JavaScript - Size: 786 KB - Last synced at: 14 days ago - Pushed at: 15 days ago - Stars: 0 - Forks: 0
siboehm/lleaves
Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.
Language: Python - Size: 4.74 MB - Last synced at: 13 days ago - Pushed at: 5 months ago - Stars: 412 - Forks: 33
ArunabhaPani/kaggle_house_price_prediction_advanced_regression_ml_model
started by analysing and determining the aspects required for tuning of the final ml model. Performed Eda and feature engineering inorder to determine the import parameters of the dataset and to derive more useful features, finally creating a ml model by using various different basic and advanced regression techniques.
Language: Jupyter Notebook - Size: 1.69 MB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 0 - Forks: 0
tavsszn/Algorithmic-Trading-Bot
The project aims to evaluate the predictive performance of different machine learning (ML) algorithms for Bitcoin trading. The proposed trading strategy integrates key technical indicators, including the Relative Strength Index (RSI), Simple and Exponential Moving Averages, and the Moving Average Convergence Divergence (MACD).
Language: JavaScript - Size: 813 KB - Last synced at: 16 days ago - Pushed at: 16 days ago - Stars: 0 - Forks: 0
harishkumaarhk/Algorithmic-Trading-Bot
The-project-aims-to-evaluate-the-predictive-performance-of-different-machine-learning-(ML)-algorithms-for-Bitcoin-trading.-The-proposed-trading-strategy-integrates-key-technical-indicators,-including-the-Relative-Strength-Index-(RSI),-Simple-and-Exponential-Moving-Averages,-and-the-Moving-Average-Convergence-Divergence-(MACD).
Size: 2.93 KB - Last synced at: 16 days ago - Pushed at: 17 days ago - Stars: 0 - Forks: 0
mohamed51152/Algorithmic-Trading-Bot
The project aims to evaluate the predictive performance of different machine learning (ML) algorithms for Bitcoin trading. The proposed trading strategy integrates key technical indicators, including the Relative Strength Index (RSI), Simple and Exponential Moving Averages, and the Moving Average Convergence Divergence (MACD).
Size: 2.93 KB - Last synced at: 16 days ago - Pushed at: 17 days ago - Stars: 0 - Forks: 0
ANGEL12221/Algorithmic-Trading-Bot
The project aims to evaluate the predictive performance of different machine learning (ML) algorithms for Bitcoin trading. The proposed trading strategy integrates key technical indicators, including the Relative Strength Index (RSI), Simple and Exponential Moving Averages, and the Moving Average Convergence Divergence (MACD).
Size: 2.93 KB - Last synced at: 16 days ago - Pushed at: 17 days ago - Stars: 0 - Forks: 0
timowilm1992/MultiLGBM
🌳MultiLGBM🌳: A simple multi-objective regression example to show how to trade-off objectives on the Pareto front with a single LGBM model.
Language: Python - Size: 10.4 MB - Last synced at: 18 days ago - Pushed at: 18 days ago - Stars: 12 - Forks: 0
jeongukjae/lightgbm-serving
A lightweight server for LightGBM
Language: C++ - Size: 780 KB - Last synced at: 13 days ago - Pushed at: over 4 years ago - Stars: 16 - Forks: 7
microsoft/lightgbm-transform
Transformation library for LightGBM
Language: C++ - Size: 4.17 MB - Last synced at: 6 days ago - Pushed at: over 1 year ago - Stars: 34 - Forks: 8
aws-samples/amazon-sagemaker-local-mode
Amazon SageMaker Local Mode Examples
Language: Python - Size: 5.94 MB - Last synced at: 17 days ago - Pushed at: 2 months ago - Stars: 255 - Forks: 61
AdrianAntico/AutoQuant
R package for automation of machine learning, forecasting, model evaluation, and model interpretation
Language: R - Size: 804 MB - Last synced at: about 4 hours ago - Pushed at: 4 months ago - Stars: 243 - Forks: 43
saivasanthg/NLP-based-Disaster-Detection-in-Tweets-using-ML-Algorithms
This project focuses on detecting disaster-related tweets using machine learning. The dataset, sourced from Kaggle, contains 7613 tweets labeled as disaster-related or not. Various Natural Language Processing (NLP) techniques and machine learning models were applied to classify these tweets accurately.
Language: Jupyter Notebook - Size: 466 KB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 0 - Forks: 0
TeamHG-Memex/eli5
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Language: Jupyter Notebook - Size: 35.7 MB - Last synced at: 13 days ago - Pushed at: almost 3 years ago - Stars: 2,770 - Forks: 331
cerlymarco/shap-hypetune
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
Language: Jupyter Notebook - Size: 122 KB - Last synced at: 19 days ago - Pushed at: 11 months ago - Stars: 577 - Forks: 73
ClimbsRocks/auto_ml
[UNMAINTAINED] Automated machine learning for analytics & production
Language: Python - Size: 1.38 MB - Last synced at: 13 days ago - Pushed at: about 4 years ago - Stars: 1,644 - Forks: 312
gabrielpreda/Kaggle
Kaggle Kernels (Python, R, Jupyter Notebooks)
Language: Jupyter Notebook - Size: 249 MB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 36 - Forks: 18
CelineBoutinon/credit-scoring
Source code for OpenClassrooms - Data Scientist Project 7 - Implement a Scoring Model
Language: HTML - Size: 27.8 MB - Last synced at: 22 days ago - Pushed at: 22 days ago - Stars: 0 - Forks: 0
FouetteBytes/Data_Crunch_106
Time series forecasting solution for predicting agricultural climate variables in Harveston using ensemble LightGBM models with advanced feature engineering. Our approach combines temporal, geographical, and meteorological features to accurately predict temperature, radiation, rainfall, and wind patterns for agricultural planning.
Language: Jupyter Notebook - Size: 7.36 MB - Last synced at: 17 days ago - Pushed at: 22 days ago - Stars: 1 - Forks: 0
HuangCongQing/AI_competitions
AI比赛相关信息汇总
Size: 75.2 KB - Last synced at: 22 days ago - Pushed at: about 2 years ago - Stars: 633 - Forks: 124
alessioborgi/MLPipeline_OptimizationStudy
Exploration and optimization of a ML pipeline, delving into various techniques for enhancing different stages of ML workflows, including data preprocessing, feature engineering, model selection, and hyperparameter tuning.
Size: 6.84 KB - Last synced at: 23 days ago - Pushed at: 23 days ago - Stars: 0 - Forks: 0
ThomasBury/arfs
All Relevant Feature Selection
Language: Python - Size: 77.6 MB - Last synced at: 15 days ago - Pushed at: 23 days ago - Stars: 131 - Forks: 14
thaochu05/March_Machine_Learning_Mania_2025
🏀 Predicting NCAA tournament outcomes using historical team data and LightGBM models. Built for Kaggle's March Machine Learning Mania 2025 - includes EDA, feature engineering, and model building with a Brier score of 0.126.
Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: 23 days ago - Pushed at: 23 days ago - Stars: 0 - Forks: 0
StatMixedML/LightGBMLSS
An extension of LightGBM to probabilistic modelling
Language: Python - Size: 32 MB - Last synced at: 22 days ago - Pushed at: 11 months ago - Stars: 299 - Forks: 31
sametcopur/treemind
treemind interprets ensemble tree models by analyzing individual trees and their predictions, providing insights into the decision-making process.
Language: Python - Size: 373 MB - Last synced at: about 5 hours ago - Pushed at: 3 months ago - Stars: 22 - Forks: 2
suzuran0y/house-price-regression-prediction
Predicting house prices using advanced regression techniques (Kaggle competition solution with model stacking & feature engineering).
Language: Python - Size: 3.98 MB - Last synced at: 25 days ago - Pushed at: 25 days ago - Stars: 0 - Forks: 0
DeepWisdom/AutoDL
Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.
Language: Python - Size: 4.46 MB - Last synced at: 19 days ago - Pushed at: over 2 years ago - Stars: 1,155 - Forks: 215
Yahlawat/Credit-Card-Default-Prediction
Predicting default payments using gradient boosting and ensemble machine learning models. Includes EDA, model comparison (Random Forest, XGBoost, LightGBM, etc.), ROC analysis, and feature importance on Taiwanese credit card client data.
Language: Jupyter Notebook - Size: 784 KB - Last synced at: 26 days ago - Pushed at: 26 days ago - Stars: 0 - Forks: 0
ccomkhj/interpretable-lightgbm
SHAP explainer for LightGBM models - Generate feature importance plots, dependence plots, and prediction explanations with one line of code. Make your gradient boosting models interpretable for stakeholders.
Language: Python - Size: 0 Bytes - Last synced at: 27 days ago - Pushed at: 27 days ago - Stars: 0 - Forks: 0
hyunjoonbok/Python-Projects
Portfolio in Python
Language: Jupyter Notebook - Size: 43 MB - Last synced at: 10 days ago - Pushed at: almost 2 years ago - Stars: 44 - Forks: 14
adeniyigiwa/modelmirror
⚖️ ModelMirror – Audit ML models for fairness, bias, leakage & explainability. Upload your model, see the truth. Built with Streamlit.
Language: Python - Size: 5.86 KB - Last synced at: 28 days ago - Pushed at: 28 days ago - Stars: 0 - Forks: 0
jrzaurin/LightGBM-with-Focal-Loss
An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems
Language: Python - Size: 24.4 KB - Last synced at: 26 days ago - Pushed at: over 5 years ago - Stars: 251 - Forks: 40
linkedin/FastTreeSHAP
Fast SHAP value computation for interpreting tree-based models
Language: Python - Size: 152 MB - Last synced at: 17 days ago - Pushed at: almost 2 years ago - Stars: 537 - Forks: 34
pyramidheadshark/customer-churn-interactive-research
Interactive customern churn research utilizing lightgbm made for practice
Language: Jupyter Notebook - Size: 5.94 MB - Last synced at: 7 days ago - Pushed at: about 1 month ago - Stars: 2 - Forks: 0
nikitakunz/Optiver-Kaggle-Competition
Predicting the closing price movements for hundreds of Nasdaq listed stocks using data from the order book and the closing auction of the stock.
Language: Jupyter Notebook - Size: 20.5 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0
auto-flow/auto-flow
AutoFlow : Automatic machine learning workflow modeling platform
Language: Python - Size: 12.3 MB - Last synced at: about 11 hours ago - Pushed at: over 3 years ago - Stars: 67 - Forks: 6
orchardbirds/bokbokbok
Custom Loss Functions and Evaluation Metrics for XGBoost and LightGBM
Language: Python - Size: 574 KB - Last synced at: 4 days ago - Pushed at: 12 days ago - Stars: 36 - Forks: 7
microsoft/DMTK 📦
Microsoft Distributed Machine Learning Toolkit
Size: 16.6 KB - Last synced at: 6 days ago - Pushed at: over 6 years ago - Stars: 2,749 - Forks: 558
jiangnanboy/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。Use LightGBM to learn ranking, including data processing, model training, model decision visualization, model interpretability and prediction, etc.
Language: Python - Size: 2 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 265 - Forks: 71
owenodriscoll/AutoML
Python package for automated hyperparameter-optimization of common machine-learning algorithms
Language: Python - Size: 3.26 MB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 4 - Forks: 1
catboost/benchmarks
Comparison tools
Language: Jupyter Notebook - Size: 43.3 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 170 - Forks: 47
searchpioneer/ranking-cli
A command line tool for training and evaluating ranking models using LightGBM and FastTree
Language: C# - Size: 33.2 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
SevilayMuni/LGBM-homicide-prediction-app
LightGBM ML application deployment via Streamlit.
Language: Jupyter Notebook - Size: 10.4 MB - Last synced at: 23 days ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
xiaodaigh/JLBoost.jl
A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms
Language: Julia - Size: 277 KB - Last synced at: about 1 month ago - Pushed at: 5 months ago - Stars: 73 - Forks: 6
cgreer/alpha-zero-boosted
A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)
Language: Python - Size: 428 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 86 - Forks: 12
StatMixedML/DGBM
Distributional Gradient Boosting Machines
Size: 169 KB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 26 - Forks: 1
bits-bytes-nn/mofc-demand-forecast
Time Series Forecasting for the M5 Competition
Language: Jupyter Notebook - Size: 3.08 MB - Last synced at: 24 days ago - Pushed at: over 3 years ago - Stars: 40 - Forks: 10
sefaerkan/Backpack-Price-Prediction
Predict the price of backpacks given various attributes
Language: Python - Size: 0 Bytes - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
Opt-Mucca/PySCIPOpt-ML
Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs
Language: Python - Size: 2.54 MB - Last synced at: 13 days ago - Pushed at: about 2 months ago - Stars: 26 - Forks: 0
gillemta/bug-likelihood-ranker
A Python tool employing a LightGBM-based Learning-to-Rank approach to predict and rank source code files by their bug likelihood.
Language: Python - Size: 688 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
ccao-data/lightsnip
Hard fork of curso-r/treesnip specifically for CCAO LightGBM regressions
Language: R - Size: 21.9 MB - Last synced at: 11 days ago - Pushed at: about 2 months ago - Stars: 2 - Forks: 0
canerturkseven/ForecastFlowML
🧙 Scalable machine learning forecasting framework with Pyspark
Language: Python - Size: 152 MB - Last synced at: 9 days ago - Pushed at: almost 2 years ago - Stars: 5 - Forks: 1
atfortes/Repeat-Buyers-Prediction
Alibaba Cloud | Tianchi Competition: TMALL Repeat Buyers Prediction Top 0.7% Solution
Language: Jupyter Notebook - Size: 6.28 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
rickiepark/handson-gb
XGBoost와 사이킷런으로 배우는 그레이디언트 부스팅
Language: Jupyter Notebook - Size: 185 MB - Last synced at: 16 days ago - Pushed at: about 2 months ago - Stars: 25 - Forks: 21
RektPunk/MQBoost
Multiple quantiles estimation model maintaining non-crossing condition (or monotone quantile condition) using LightGBM and XGBoost
Language: Python - Size: 752 KB - Last synced at: about 1 month ago - Pushed at: 5 months ago - Stars: 29 - Forks: 5
milenkovicm/lightfusion
LightGBM Inference on Datafusion
Language: Rust - Size: 9.83 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0
kapsner/mllrnrs
Learners for the `mlexperiments` R 📦
Language: R - Size: 322 KB - Last synced at: 3 days ago - Pushed at: about 2 months ago - Stars: 2 - Forks: 0
jrzaurin/ml-pipeline
Using Kafka-Python to illustrate a ML production pipeline
Language: Jupyter Notebook - Size: 19.8 MB - Last synced at: 12 days ago - Pushed at: over 2 years ago - Stars: 109 - Forks: 51
neptune-ai/open-solution-mapping-challenge
Open solution to the Mapping Challenge :earth_americas:
Language: Python - Size: 704 KB - Last synced at: 2 days ago - Pushed at: about 4 years ago - Stars: 386 - Forks: 97
mljar/supertree
Visualize decision trees in Python
Language: Python - Size: 38.7 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 481 - Forks: 14
Trangy-star/IPL-Win-Predictor
A machine learning model that predicts the outcome of IPL matches based on historical data and player performance. Built using Python and libraries like Pandas, NumPy, and scikit-learn. This project demonstrates the use of classification algorithms to predict match outcomes.
Size: 1.95 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
lunayht/uplift-modelling
Uplift modelling using meta learners
Language: Jupyter Notebook - Size: 257 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
debjitpal5040/ML_Algorithms
A repository for almost every machine learning algorithms
Language: Jupyter Notebook - Size: 63.6 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 1
