Setup:

1. Download the 'All India Air Quality Data.csv' from the following link: https://drive.google.com/drive/folders/12CoOmE5SN8p_hkLUV4B16e9DsKbuK5kQ?usp=sharing

2. Place the downloaded dataset in the following manner: AirPol\India\All India Air Quality Data.csv

3)You're ready to go.

Dependencies:

• Python 3.7
• Tensorflow = 2.x.x
• Scikit Learn
• Matplotlib
• Seaborn
• Numpy
• Pandas
• Scipy

AirPol

AirPol is a project that aims to use various meteorological, geographical and current air pollutant concentration to predict accurate future concentration of air pollutants in advance.

The current work has succesfully conducted a comparative study between various estimators to predict the air pollutant concentration. The algorithms considered during the comparative study were:

1. Linear Regression
2. Stochastic Gradient Descent
3. Neural Network
4. Decision Tree Regression
5. Boosted Decision Tree Regression
6. Random Forest
7. Boosted Random Forest Regression

Other data analysis included splitting the dataset according to seasons, including and excluding meteorological factors etc.

For any queries contact me: [email protected]