Smart Weather Energy Prediction System

Developed a Smart Weather Energy Prediction System using Machine Learning to analyze weather-related data and predict energy-related outcomes.

The project focuses on data preprocessing, exploratory data analysis, feature engineering, and machine learning model development to identify patterns between weather conditions and energy consumption or generation.

Python and data science techniques were used to process the dataset, build predictive models, evaluate their performance, and generate useful predictions from weather data.