India is one of the higher air pollution country. Generally, air pollution is assessed by PM value or air quality index value. For my further analysis, I have selected PM-2.5 value to determine the air quality prediction and India-Bangalore region. Also, the data was collected through web scraping with the help of Beautiful Soup.
Air quality data was collected from the "http://en.tutiempo.net/climate". So, here I selected the India- Bangalore'sregion & collected the independent features such as Average annual temperature(AT), Annual average maximum temperature(TM), Average annual minimum temperature(Tm), Rain or snow precipitation total annual(PP), Annual average wind speed(V), Number of days with rain(RA), Number of days with snow(SN) and dependent feature as PM 2.5 values has been colected from the "dhewdhjwdhjw"
The dataset used can be downloaded Here from the 2013 to 2018.
Technologies Used :
- IDE - Pycharm
- Linear Regression Model
- Ridge and Lasso Regression
- Support vector regressor(SVR)
- Extra tree regressor
- Decission tree regressor
- Google Colab - Trained ML model
- Flask- Rest API
Installation Step : -
- python 3.8.0
- command 1 - python -m pip install --user -r requirements.txt
- command 2 - python app.py