lightgbm-regressor
There are 55 repositories under lightgbm-regressor topic.
toshi-k/kaggle-santa-2020
9th place solution in "Santa 2020 - The Candy Cane Contest"
Mechres/Price-Predict
Crypto & Stock* price prediction with regression models.
Erdos1729/food-demand-forecasting
This repository will work around solving the problem of food demand forecasting using machine learning.
nipun-goyal/Residential-Energy-Consumption-Prediction
Predicting the Residential Energy Usage across 113.6 million U.S. households using Machine Learning Algorithms (Regression and Ensemble)
eitansela/eitans-sagemaker-examples
Amazon SageMaker Examples
Pratik94229/Retail-Sales-Prediction---End-to-End-Project
This repository contains code and resources for an end-to-end regression project on retail sales prediction. The goal of this project is to develop a regression model that can accurately predict retail sales based on various features.
Aishwaryakkumar/Automobile
Automobile dataset for used Car Price Analysis to predict the price of a vehicle with their features and performance factor to provide the exact value of a vehicle for buyer seller satisfaction using exploratory data analysis and machine learning models.
caiocasagrande/taxi
Projeto de previsões de pontos de chegada em corridas de táxi na cidade do Porto, Portugal.
kyaiooiayk/LightGBM-Notes
Notes, tutorials, code snippets and templates focused on LightGBM for Machine Learning
opsabarsec/IoT_timeseries_analysis
Analysis of time series data from IoT devices
Rjt5412/Elo-Merchant-Category-Recommendation
A Machine Learning Case Study based on helping the company target customers by predicting the customer loyalty score based on the transactions data.
stephenllh/m5-accuracy
Silver medal solution for the "M5 Forecasting - Accuracy" Kaggle competition
tohid-yousefi/Machine_Learning_Algorithms_for_Time_Series_Analysis_Total_Trading_Volume_Forecasting
In this section, we will use machine learning algorithms to perform time series analysis.
6mini/cother19
☀️ 데이터 파이프라인 프로젝트 기상으로 예측하는 서울시 코로나 확진자 수 앱 😷
bagusganjarl/used-car-auction-prices
A final project of Data Science Bootcamp Batch 20 in Rakamin Academy.
deleusis/Data-Science-Gradient-Boosting
Using LightGBM and Other Models for Car Prices' Prediction – Study Project for Yandex Practicum
denis-42ds/demand_forecast_retailer
creation of an interface and algorithm for forecasting demand for 14 days for goods of own production
Denis-Mukhanov/forecast-of-taxi-orders
Yandex Practicum Data Science project
dfavenfre/Bike-Sharing-Demand-Prediction
Bike Rent Demand Prediction Model
farazkhancodes/Predictive-Modelling-of-Multimodal-Single-Cell-Genomic-Data-with-Machine-Learning-Algorithms
This code demonstrates the use of machine learning to model the multimodal nature of a single cell. Using machine learning to predict RNA from DNA, that is, using chromatin accessibility data to predict the RNA gene expression and to predict surface protein from RNA, that is, using RNA sequence data to predict surface protein levels in a cell
hperer02/Automated-essay-scoring
This repository contains my solution for the Kaggle competition Automated Essay Scoring 2.0. The goal of this project is to develop an automated system capable of scoring essays based on their content and quality using machine learning techniques.
jiatangzhi/r_stock_market_prediction
Predict stock returns using ARIMA and LightGBM to analyze historical data and uncover key drivers with feature importance in this financial forecasting project.
m3xw3ll/LightGBM
Examples using LightGBM for several ML tasks
nlawira/india-house-rent-prediction
This repository contains a project I completed for an NTU course titled CB4247 Statistics & Computational Inference to Big Data. In this project, I applied regression and machine learning techniques to predict house prices in India.
SerhatDerya/House-Prices---Advanced-Regression-Techniques
This machine learning model was developed for "House Prices - Advanced Regression Techniques" competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.
yyigitturan/Baseball-Players-Salary-Prediction
This project develops a machine learning model to predict the salaries of baseball players based on their past performance.
Al-1n/Gradient_Boosting_Tuning
Evaluating Hyperopt, Optuna, and TunedThresholdClassifierCV
aranzadata/CarPricePredictor
Se desarrolló un modelo de predicción de precios de autos con una precisión de 0,84 y un tiempo de predicción de 1 segundo,
ManafMukred/Time_Series_forcasting_and_Anomaly_Detection
This project aims to predict Wind Turbine output power and searches for any anomalies
pabloelt/risk-scoring-for-a-neobank-company
A risk-scoring model is developed for a bank company using machine learning algorithms to assess the profitability of new loan applicants. The model predicts Expected Loss by analyzing Probability of Default, Exposure at Default, and Loss Given Default.
pabloelt/sales-forcasting-for-a-retail-company
Sales Forecasting for a Retail Company. A forecasting model is developed to reduce warehouse costs and stock-outs by using a scalable set of recursive machine learning algorithms. This model predicts demand for the next 8 days at a store-product level, based on the historical company’s data.
RafaRomanS/Green-Light-proyecto-
Este fue el proyecto final del Bootcamp de Data Science y Machine & Deep Learning, fue desarrollado junto con mi compañero Pablo Pita. Este proyecto trata de predecir el consumo y la produccion de clientes con placas solares, en el enlace podréis ver la presentación que realizamos
Samidullo-Abdullayev/Flights_Arrival_Delay_regression-
This project aims to predict flight arrival delays using various machine learning algorithms. It involves EDA, feature engineering, and model tuning with XGBoost, LightGBM, CatBoost, SVM, Lasso, Ridge, Decision Tree, and Random Forest Regressors. The goal is to identify the best model for accurate predictions.