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THIS WEB_APP ALLOWS USER TO PREDICT THE AIR QUALITY INDEX BASED ON FEATURES LIKE TEMPERATURE, WIND VELOCITY, ATMOSPHERIC PRESSURE

License: MIT License

Python 89.51% HTML 4.82% Dockerfile 1.40% HCL 4.27%
air-quality machine-learning dvc-pipeline xgboost

air_quality_index_prediction's Introduction

AIR_QUALITY_INDEX_PREDICITON

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The project is about creating a model which predicts the flight fare price based on factors like distance, number of stops, total hours of flight as well as the type of seat

Here are the screenshots of working example on an AWS Linux Instance.

Table of contents



Usage

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Man pages have been added. Checkout man colorls.

Installation

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  1. Install git (preferably, version >= 2.0) and python (preferably, version >=3.6) (windows) For Linux :
   sudo yum instal git -y
   sudo yum install python -y
  1. Copy the github url from the repository :
https://github.com/SiddharthaShandilya/air_quality_index_prediction.git
  1. Select a Directory in local system and use
git clone https://github.com/SiddharthaShandilya/air_quality_index_prediction.git           
*Note for `git clone command`  Please make sure that you have proper internet connection. *

*Note for `python` Please try to anaconda for running the app.*  
  1. Create a seperate virtual environment to avoid conflict between python libraries :
    python3 -m venv new-env 
  1. Activate the virtual env: ๐Ÿ‘‰ (click Here)
  2. Install all the libraries for the application.
pip3 install -r requirements.txt
  1. Have a look at Recommended configurations and Custom configurations.



Recommended configurations

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