A machine learning model for predicting weather conditions based on historical and real-time data. This project provides accurate predictions for temperature, rainfall, humidity, and other weather parameters.
The Weather Prediction Model uses supervised machine learning techniques to forecast weather conditions. The model leverages historical weather datasets and incorporates features like temperature, humidity, wind speed, and atmospheric pressure to provide short-term and medium-term weather predictions.
The goal is to assist individuals, businesses, and organizations in making informed decisions based on predicted weather trends.
- Predicts rainfall with wind direction, humidity, and wind speed.
- random forest algorithm and logistic regression is used
- Built-in feature importance analysis to explain predictions.
Programming Language: Python Libraries: NumPy Pandas Scikit-learn Matplotlib/Seaborn (for visualization)