⚡ Energy Consumption Prediction

This project explores energy consumption prediction using machine learning techniques such as Random Forest, with a focus on data preprocessing, feature engineering, and model evaluation.

📊 Project Goals

• Analyze and visualize energy-related data.
• Build predictive models for forecasting consumption.
• Evaluate and compare model performance.
• Provide clean code and visuals within a Jupyter notebook.

🧪 Technologies Used

• Python 3.x
• pandas, numpy
• matplotlib, seaborn
• scikit-learn
• Jupyter Notebook

🚀 How to Use

1. Clone the repository:

git clone https://github.com/yourusername/energy-forecast-notebook.git
cd energy-forecast-notebook

## Install the dependencies:
pip install -r requirements.txt

## Launch the notebook
jupyter notebook energy_forecast.ipynb