#PM2.5-Prediction

Description: This ML based project predicts that how the value of PM2.5 varied on different factors such as temperature,pressure,wind-direction,wind-speed,and rain. EDA ,data cleaning ,feature selection,cross validation and hyper tuning is performed on the dataset.Deployment of this project is done using flask. Various libraries like numpy,pandas,Sci-Kit,matplotlib,seaborn,pickle are used in this project.

Requirements to run the project: ->Editor(eg. vscode) ->Jupyter notebook and all its libraries extensions like pandas,numpy,etc. ->Python ->html,css

How To Use: First add all these files in a folder and open the folder in your editor(eg: vscode). Once you open the folder explore the final project python file and run it, this can take some 12 to 14 minutes because of hyperparameter tuning(wait patiently). next thing you need to do is open the app.py file and run it. After running , open the terminal , a link will appear at the end of the terminal.Copy that link and run it on your browser.A web page will appear, enter the values (you can take samples from the dataset) and on pressing 'predict' you will get the value of PM2.5 .