Popular GitHub Repositories for Xgboost Regression

Building Time series forecasting models, including the XGboost Regressor, GRU (Gated Recurrent Unit), LSTM (Long Short-Term Memory), CNN (Convolutional Neural Network), CNN-LSTM, and LSTM-Attention. Additionally, hybrid models like GRU-XGBoost and LSTM-Attention-XGBoost for Electricity Demand and price prediction

The "House Price Prediction" project focuses on predicting housing prices using machine learning techniques. By leveraging popular Python libraries such as NumPy, Pandas, Scikit-learn (sklearn), Matplotlib, Seaborn, and XGBoost, this project provides an end-to-end solution for accurate price estimation.

Crypto & Stock* price prediction with regression models.

Serverless ML system to predict the direction and volume of electricity flows to and from the Netherlands and its energy transmission partners.

Drift Detection in Gas Sensor Array at Different Concentration Levels ☢️

The proposed model is able to predict the evaluation of both grammatical coherence, vocabulary and grammatical conventions, so that the evaluation can give each of those criteria a value between 1 and 5, I did not treat the system as a classification process, but rather it was treated as a REGRESSION issue. It includes several steps through which a few errors were reached, all ranging between 0.25 for each criterion. The values ??of the weights that were reached can also be used to deal with the issue as a classification process (but it was not dealt with as well in this proposed methodology).

Estimate Formula 1 qualifying results using ML

This repo is a part of K136. Kodluyoruz & Istanbul Metropolitan Municipality Data Science Bootcamp. The project aims to produce a machine learning model for home price estimation. The model was built on the Kaggle House Prices - Advanced Regression Techniques competition dataset.

Demonstrates how to utilize XGBoost for traffic forecasting using data gathered from IoT sensors, highlighting its efficiency in processing complex datasets and delivering accurate predictions.

Almost and AutoML around xgb, catboost and lightgbm

This repository contains code to perform EDA, outlier detection and forcasting on a multivariate time series.

Nonlinear Regression Models

为了方便复现论文《基于梯度提升方法的共享微出行需求预测》（发表于2025年EDBT/ICDT联合会议研讨会论文集（BMDA研讨会））的结果，提供了相应的材料（源代码和数据）。