tstran155/Optimization-of-building-energy-consumption

This repo demonstrates how to build a surrogate (proxy) model by multivariate regressing building energy consumption data (univariate and multivariate) and use (1) Bayesian framework, (2) Pyomo package, (3) Genetic algorithm with local search, and (4) Pymoo package to find optimum design parameters and minimum energy consumption.

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esvs2202/Concrete-Compressive-Strength-Prediction

The aim of this project is to develop a solution using Data science and machine learning to predict the compressive strength of a concrete with respect to the its age and the quantity of ingredients used.

Language: Jupyter Notebook - Size: 4.54 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 18 - Forks: 9

holukas/diive

Time series processing library

Language: Python - Size: 837 MB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 13 - Forks: 2

abhinav-bhardwaj/Walmart-Sales-Time-Series-Forecasting-Using-Machine-Learning

Time Series Forecasting of Walmart Sales Data using Deep Learning and Machine Learning

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banzuzi-carioni/cross-border-electricity-flow-prediction

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

Language: Python - Size: 44 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 11 - Forks: 0

Dalageo/ML-GasSensorDrift

Drift Detection in Gas Sensor Array at Different Concentration Levels ☢️

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RezaSaadatyar/Time-Series-Analysis-in-Python

This repository contains Python functions for predicting time series.

Language: Python - Size: 1.51 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 11 - Forks: 0

ashishrana1501/Forest-Fire-Prediction

Algerian Forest Fire Prediction

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shreyaswankhede/Airbnb_Rental_Price_Prediction

The objective of this project is to model the prices of Airbnb appartments in London.The aim is to build a model to estimate what should be the correct price of their rental given different features and their property.

Language: Python - Size: 5.2 MB - Last synced at: about 1 month ago - Pushed at: about 6 years ago - Stars: 8 - Forks: 3

Mechres/Price-Predict

Crypto & Stock* price prediction with regression models.

Language: Python - Size: 768 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 7 - Forks: 1

MitchellTesla/Max-Q Fork of arXiv-research/Quatm

Machine-Learning: eXtreme Gradient-Boosting Algorithm Stress Testing

Language: C++ - Size: 155 MB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 7 - Forks: 0

xiaorancs/chicken-sales-forecast

回归预测

Language: Python - Size: 284 KB - Last synced at: about 1 month ago - Pushed at: over 7 years ago - Stars: 7 - Forks: 2

Anamicca23/Muli-Class-Obesity-Risk-Level-Prediction-Project-using-ML

Advancing Healthcare with 91% Accurate Prediction of Obesity Risk Levels Using XGBoost ,LightGBMand CatBoostClassifier Model

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aayush1036/housing-rent-prediction

End to End Machine Learning Project along with deployment.

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aws-samples/amazon-sagemaker-xgboost-regression-model-monitor-and-alerting

How to train, deploy and monitor a XGBoost regression model in Amazon SageMaker and alert using AWS Lambda and Amazon SNS. SageMaker's Model Monitor will be used to monitor data quality drift using the Data Quality Monitor and regression metrics like MAE, MSE, RMSE and R2 using the Model Quality Monitor.

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Erdos1729/food-demand-forecasting

This repository will work around solving the problem of food demand forecasting using machine learning.

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manashpratim/Big-Mart-Sales-Prediction

Predicting the sales of a store

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tmalik1116/F1_Qualifying_Predictor_ML

Estimate Formula 1 qualifying results using ML

Language: Python - Size: 162 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 4 - Forks: 1

sushant1827/Traffic-Forecasting-using-IoT-Sensor-Data

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.

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shubham5027/Store-Item-Demand-Forcasting

The "Sales Demand Forecasting Regression Model" project aims to develop a predictive model that forecasts future sales demand based on historical data and relevant influencing factors. The project follows a structured approach, encompassing data collection, preprocessing, model selection, training, evaluation, and deployment.

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coderjolly/player-market-value-prediction

There is an intense transfer speculation that surrounds all major player transfers today. An important part of negotiations is predicting the fair market price for a player. Therefore, we are predicting this Market Value of a player using the data provided in csv format.

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gitzaidi/Prediction-of-volatility-in-stock-movements-on-the-US-market

Answer to CFM challenge US-Stock-Market volatility prediction - Ranked 4th

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izelcelikkaya/housepriceprediction

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.

Language: Python - Size: 9.84 MB - Last synced at: 8 months ago - Pushed at: about 3 years ago - Stars: 4 - Forks: 10

aws-samples/amazon-sagemaker-xgboost-regression-model-hosting-on-amazon-ecs-fargate-and-amazon-api-gateway

How to train a XGBoost regression model on Amazon SageMaker, host inference on a Docker container running on Amazon ECS on AWS Fargate and optionally expose as an API with Amazon API Gateway.

Language: Jupyter Notebook - Size: 955 KB - Last synced at: about 2 months ago - Pushed at: almost 4 years ago - Stars: 4 - Forks: 2

aws-samples/amazon-sagemaker-xgboost-regression-model-hosting-on-aws-lambda-and-amazon-api-gateway

How to train a XGBoost regression model on Amazon SageMaker, host inference on a serverless function in AWS Lambda and optionally expose as an API with Amazon API Gateway

Language: Jupyter Notebook - Size: 941 KB - Last synced at: about 2 months ago - Pushed at: almost 4 years ago - Stars: 4 - Forks: 2

artisan1218/Recommendation-System

Hybrid RecSys, CF-based RecSys, Model-based RecSys, Content-based RecSys, Finding similar items using Jaccard similarity

Language: Python - Size: 63 MB - Last synced at: over 2 years ago - Pushed at: about 4 years ago - Stars: 4 - Forks: 1

nidragedd/udadsnd-p4-airbnb_inside

Udacity DataScience nanodegree 4th project: pick a dataset, explore it and write a blog post

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hasanulmukit/EcoSphereAI Fork of mmfarabi/EcoSphereAI

EcoSphereAI is a sustainable, AI-driven platform optimizing connectivity systems with features like energy optimization, predictive maintenance, and sustainability reporting. Build the future of efficient and green networks!

Language: Python - Size: 35.5 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 3 - Forks: 0

miltiadiss/CEID_NE577-5G-Architectures-Technologies-Applications-and-Key-Performance-Indexes

This project involves predicting the downlink bitrate of mobile devices in 5G networks using machine learning (XGBoost Regressor) and deep learning (LSTM model). It includes data preprocessing, training and evaluation of the models, applying explainable AI (XAI) techniques such as SHAP, and optimizing feature selection based on XAI insights.

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sparsh0106/Regression-Analysis-of-Ecommerce-Customers

Regression Analysis of Ecommerce Customers Dataset using Linear Regression and XGBRegressor

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shaadclt/Home-Price-Prediction-Economic-Indicators

This project aims to predict home prices using various economic indicators from the Federal Reserve Economic Data (FRED). The project involves data collection, data preparation, model building, and analysis of the results.

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GeorgeBatch/moleculenet

MSc Dissertation: Estimating Uncertainty in Machine Learning Models for Drug Discovery

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shubham5027/Store-Item-Demand-Crypto-Price-Prediction-using-Multiple-Time-Series-Forecasting

l train and evaluate multiple time-series forecasting models using the Store Item Demand Forecasting Challenge dataset from Kaggle. This dataset has 10 different stores and each store has 50 items, i.e. total of 500 daily level time series data for five years (2013–2017).

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AtharvaKulkarniIT/ParkinsonsTelemonitoringInsights

This R-based data science project on the UCI Parkinson's dataset employs machine learning (Decision tree, Random Forest, SVM, XGBoost) with a focus on hyperparameter tuning and feature selection. This repository showcases insights into Parkinson's disease prediction using effective data science practices.

Language: R - Size: 1.24 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 3 - Forks: 1

WalidAlsafadi/House-Prices

Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.

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Jesus-Vazquez-A/Insurence

We solve a regression problem in which it consists of calculating the health insurance charge in the United States Where we will break down the project into 5 phases: Exploratory Analysis. Feature Engineering. Selection of the ideal model. Development of the final model. Creation of a web application in streamlit.

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dgovor/Housing-Price-Prediction-Python

Machine Learning model for price prediction using an ensemble of four different regression methods.

Language: Python - Size: 286 KB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 3 - Forks: 0

aws-samples/amazon-sagemaker-xgboost-regression-model-hosting-on-aws-app-runner

How to train a XGBoost regression model on Amazon SageMaker and host inference as an API on a Docker container running on AWS App Runner.

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Collinjia/NLP-CLRP-Contest

Kaggle NLP competition : Rate the complexity of text using BERT

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ItsTSH/Customer-Churn-Prediction

Customer Churn Prediction System using XGBoost Regressor, built on Telecom Industry dataset

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davutbayik/food-delivery-time-prediction

Food Delivery Time Prediction using Machine Learning Techniques

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dcrey7/fifa19-web-app

Fifa19 Web app

Language: Jupyter Notebook - Size: 12 MB - Last synced at: 4 months ago - Pushed at: 5 months ago - Stars: 2 - Forks: 0

datalopes1/flight_prices

Projeto de Regressão Linear utilizando o XGBRegressor, com base no dataset Flight Price Prediction de Shubham Bathwal e disponibilizado no Kaggle

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Efesasa0/GDZ-elektrik-timeseries

Almost and AutoML around xgb, catboost and lightgbm

Language: Python - Size: 22.2 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 1

samagra44/Zomato_Delivery_Time_Prediction

The Zomato Delivery Time Prediction Application is a machine learning-driven Flask web application designed to predict the estimated delivery time for food orders placed on the Zomato platform.

Language: Python - Size: 4.32 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

alexdatadesign/lfp_soc_ml

LiFePo4(LFP) Battery State of Charge (SOC) estimation from BMS raw data

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LuluW8071/Laptop-Price-Prediction

A collection of machine learning models for predicting laptop prices

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Harish-or-Peter/Appliance-Energy-Prediction

Predicted residential energy consumption using Linear Regression, Random Forest, and XGBoost models. Random Forest showed best performance, offering insights into energy usage patterns. Code and results on GitHub for reference and optimization.

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ved-et9/ipl_2023_score_predictor

🏏Predicting Ipl score on the model trained by Various ML algos 🔥,deployed the interface on hugging face for interacting with online users

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KalinNonchev/xgbexcel

Python package that converts an XGBRegressor model to an Excel formula expression.

Language: Python - Size: 28.3 KB - Last synced at: 21 days ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

fa1zali/house_price_prediction_using_xgboost_regressor

A Machine Learning project using XGBoost Regressor for predicting house prices.

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kaledhoshme123/A-proposed-model-that-can-predict-the-assessment-of-both-Syntax-Cohesion-Vocabulary-Phraseology-

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).

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ahmedshahriar/Housing-Price-Prediction

Data science project on Housing Prices Dataset regression analysis

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Rnoozy/Guessing-Prices-Pizza

Guessing the prices of pizza, this Machine Learning model using Linear Regression, and this project inspired by YouTube channel indonesia_belajar

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Katerinafomkina/House-Predicting-Advanced-Regression-Techniques

Predicting house price

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Geetika-tech19/CaloriesBurntPrediction

About Calories-Burned-Prediction Using Machine Learning. (Regression Use Case)

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Vaishnavi-vi/Household_Energy_Usage_Forecast_--

The Household Power Consumption Dataset contains measurements of electric power usage in a single household in France, collected over a period of 4 years at one-minute intervals.

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Nishant2018/Predict-Calorie-Expenditure---XGBoost

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Blacksujit/Data-thon-2025

Builded an Scalable ML Model for the E-commerce category and to determine the item accuracy for the local area stores

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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.

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debasishray16/StockPredictor

This project basically aims to provide a visual representation and comparative analysis of close price data related to different company ticker. It involves an interactive dashboard for users to display analysis and prediction of stocks data by using LSTM + XG-Boost model

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Onome-Joseph/ML-Sales-Prediction

This repository contains a Sales Prediction Machine Learning Model built to predict sales from a set of features with very high accuracy

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shahpranshu27/HandsOn_ML

This is GEM repo, as it has all the Hands-On ML notebooks

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brendanbignell/CUDA_MonteCarloOptionPricer

CUDA Monte Carlo Barrier Option Pricing Demo & Jupyer lab ML models

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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.

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ozerzeynep/KONTR_FIRMA_ANALIZ

Bu proje, Kontr firmasının borsa verilerini kullanarak hisse senedi fiyatlarının gelecekteki değerlerini tahmin etmeye yönelik gelişmiş makine öğrenimi modelleri içerir. Farklı algoritmalarla performans analizi yaparak yatırım kararlarını destekleyici öngörüler sağlar.

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Simran2911/Flight-Price-Pridiction

This github repositiory contains the Flight Price Prediction project aims to develop a machine learning model to predict flight ticket prices based on various factors such as departure and arrival locations, dates, airlines, and other relevant features.

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VIKRAM2563/HousePricePrediction-MachineLearning

Predict house prices using XGBoost regression. This project preprocesses data, trains the model, and evaluates predictions to forecast house prices based on various features.

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Harshraj1301/Meijer---Real-Estate-Predictive-Model

Developed a predictive real estate model leveraging XG Boost Regressor, integrating web-scraped market data with existing datasets to forecast daily store visits, achieving a MAPE of 13.3%, enabling strategic retail location decisions

Language: Jupyter Notebook - Size: 69.5 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

gokulnpc/BigMart-Sales-Prediction

This web app is created to predict the sales of Big Mart based on the input features provided by the user. The model used in this web app is a XGBoost Regressor model which is trained on the Big Mart Sales dataset. The dataset used in this web app is taken from the Kaggle Datastes. The dataset contains 8523 rows and 12 columns.

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bdiptesh/CodeLib

Development of new ML library

Language: Python - Size: 2.71 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 1

krunalss/data_it_enterprises

Language: Jupyter Notebook - Size: 2 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

oliveiract/Drugstore-Sales-Forecast

This repository contains files and scripts to build a sales forecasting Telegram Bot for a pharmacy chain. The purpose of this project is to quickly and easily provide a revenue estimate in order to assist the CEO in decision making. (Project Data Science in Production / DS Community)

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DHwass/XGBoost-on-Home-Data-KAGGLE

In this project, XGBoost is applied to forecast real estate prices using the Boston Housing Dataset. The primary aim is to create an effective predictive model, assess its accuracy through metrics like Mean Absolute Error (MAE), and refine its performance by tuning hyperparameters with HYPEROPT.

Language: Jupyter Notebook - Size: 220 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Sineme01/House-Rate-Predictor

House Rate Predictor

Language: Jupyter Notebook - Size: 1.78 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Yogeshpvt/Sustainable-Energy-Consumption-Analysis

Language: Jupyter Notebook - Size: 1.81 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Snigdho8869/Regression-Analysis-Projects

Repository showcasing a collection of diverse regression analysis projects including salary prediction and more.

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Axik0/OIL

Multivariate oil production time series analysis with XGBoost and neural networks

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IssamLL/Wining-Solution-ENSIAS-AI-ML-Competition

This repository contains the winning solution for the Energy Consumption Prediction Kaggle competition, securing second place.

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Abhishekkohli/ML-Projects

HousingPriceRegression.py file contains project based on linear regression. The dataset comprises values of aspects related to residential places and price of a house. TitanicClassification.py file contains project based on binary classification. The dataset comprises of data related to passengers and binary value of whether they survived or not.

Language: Python - Size: 6.84 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

hillalhar/Hourly-Energy-Consumption

Language: Jupyter Notebook - Size: 1.56 MB - Last synced at: 9 days ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

hillalhar/country-land-temperature

Language: Jupyter Notebook - Size: 4.92 MB - Last synced at: 9 days ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

arka57/Ted-Talk-Views-Prediction

Building a predictive model to predict views of Ted Talks in YouTube from dataset of past events using Machine Learning models

Language: Jupyter Notebook - Size: 3.9 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

3rd-Son/bigmart_analysis

Language: Jupyter Notebook - Size: 1.4 MB - Last synced at: 2 months ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0

dfavenfre/Bike-Sharing-Demand-Prediction

Bike Rent Demand Prediction Model

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AlaaMahmoud95/Concrete-Compressive-Strength

Regression Machine Learning Project

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hapl/predict-flight-delays

Midterm project Lighthouse Labs - Predicting flight delays project using machine learning algorithms in Python

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Sarthak061/Soil-Moisture-Pred-NITH

a machine-learning model that can predict soil moisture levels based on time series data.

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mendez-luisjose/Health-Insurance-Cost-Model

Linear Regression Health Insurance Cost Model with Different M.L. Algorithms

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MezbanS/Mercedes-Benz-Greener-Manufacturing

Reduce the time that cars spend on the test bench. Work with a dataset representing different permutations of features in a Mercedes-Benz car to predict the time it takes to pass testing. Optimal algorithms will contribute to faster testing, resulting in lower carbon dioxide emissions without reducing Mercedes-Benz’s standards.

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scalable-ml-deep-learning/predicting-snow-conditions

Predicting Snow Conditions in Passo Tonale (Trento, Italy)

Language: Python - Size: 1.84 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 1

Suhas-2002/Bengaluru-House-Price-Predictor

A Web App used to Predict House Price in Bengaluru

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kalsam123/Boston-House-price-prediction-using-regression

A machine learning web app for Boston house price prediction.

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805karansaini/AQI_Pre_v2

AQI Predictor V2 use multiple Supervised Machine Learning with Hyper tuning. ML algorithms used Linear Regressor, Lasso Regressor, Decision Tree Regressor, Random Forest Regressor, XGboost Regressor. The Model deployed on web and can predict AQI visit https://aqipredictor.up.railway.app/

Language: Python - Size: 141 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

sam-marhaendra/Car-Price-Predictor

This is a web-based application that can give a recommendation about estimated car price by inferencing its specifications.

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MafikengZ/Machine-Learning-Advanced-Regression

This project is focused on building an Advanced Linear Regression model measuring the load-shortfall-3h in Spain

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rushandgg/XGBoost_Stock_Prediction

Predict stock price direction by using XGBoost

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sanchitmisra/Bike-sharing-demand-prediction

The objective of this research is to develop a prediction model using supervised regression machine learning that support the start-up for a stable supply of rental bikes.

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DeleLinus/Supermarket-Sales-Prediction

This is a reviewed notebook to the DSN AI+ OAU July 2020 challenge where I took the first position. The project demonstrate proper Exploratory Data Analysis, categorical data handling, Data visualization, feature selection and engineering, Model selection and hyperparameter tuning of various regression algorithms.

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SF-Noorullah/Machine-Learning-with-XGBoost-and-RandomForest

Building Machine Learning Models with hyperparameter tuning by training a dataset containing more than a million rows to accurately predict the taxi trip duration in New york city

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