Rainfall Prediction ML Web App

• Create Dataset

• Using Data from https://power.larc.nasa.gov/data-access-viewer/ download the precipitation datas of major cities into cvv file which will be the dataset

• Add city names and encode them using sklearn.preprocessing OneHotEncoder()

• Standardise the data using sklearn

• Training ANN model

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• Train the model using the data

• Check for best parameters using randomise cv

• Save the final model

• Checking Model Prediction

• Check model summary, parameters, loss and accuracy

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• Test it manually on a single row

• Integrating into App

• Using streamlit make a web app and create input boxes for user input

• After taking all inputs from user, combine the input data into a Dataframe and load the model

• Feed the input Dataframe to the model and get predictions for rainfall in form of probalities

• Process these probalities to out show an output Pediction on the App

App Display

Prediction