Rain fall prediction

My rain prediction project in Australia focuses on predicting rainfall using historical weather data. The dataset includes features like temperature, humidity, wind direction, and pressure, which are used to build machine learning models. The project involves handling an imbalanced class distribution, where most observations indicate no rain. You preprocess the data using techniques like LabelEncoding, PowerTransformer scaling, and BorderlineSMOTE for oversampling. Your goal is to develop a reliable model to predict whether it will rain tomorrow, visualized through an interactive Streamlit dashboard.