Forecasting Energy Needs: Machine Learning Model for Efficient Energy Management
Statistical model and coded application that can forecast energy demands based on demographic factors. Help address climate change and global energy needs, drive economic efficiency and sustainable practices 
Using a machine learning approach, I applied a Multi-Variable Polynomial Regression to build a predictive model that estimates household energy usage based on key inputs like house size, climate and number of rooms.
By predicting future energy consumption, it helps reduce waste, optimize resource allocation, and support long-term economic and environmental goals.
