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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/

Python 63.53% HTML 23.47% Jupyter Notebook 9.54% Procfile 0.01% C 0.56% JavaScript 0.04% CSS 0.01% Lua 0.01% Cython 2.69% C++ 0.07% Fortran 0.05% Forth 0.01% Smarty 0.01% XSLT 0.01% PowerShell 0.02% Batchfile 0.01% Roff 0.01%
linear-regression machine-learning ml supervised-learning 3rd-year-project deployment developed hypertuning lasso-regression randon-forest xgboost-regression

aqi_pre_v2's Introduction

AQI_Pre_v2

you can visit AQI : https://aqipredictor.up.railway.app/

AQI Predictor v2 is better version of AQI Predictor https://github.com/805karansaini/AQI_Predictor

AQI Predictor v2 uses multiple Supervised Machine Learnings like Linear Regressor, Lasso Regressor, Decision Tree Regressor, Random Forest Regressor and XGboost Regressor along with Hyper tuning.

The Model is deployed on web and can predict AQI for New Delhi Enviroment.

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