Rain Prediction

Data Collection and Preprocessing:

• Gather historical weather data containing information about rainfall.

• Clean the data and preprocess it for training the machine learning model.

Machine Learning Model:

• Use Scikit-learn or any other machine learning library to build a predictive model. For example, you can use regression algorithms like Linear Regression, Random Forest, or Gradient Boosting to predict rainfall based on features like temperature, humidity, wind speed, etc.

Flask Application:

• Create a Flask web application to host your rain prediction model.

• Set up routes for handling requests and rendering HTML pages.

HTML and CSS:

• Design the front-end of the web application using HTML for structure and CSS for styling.