README.md

Solar Energy Production Prediction ☘

This project aims to predict solar energy production based on historical data using machine learning models.

Getting Started 😍

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites ✍🏼

Ensure you have the following installed:

• Python 3
• Required Python packages (requirements.txt)

Installing

1. Clone the repository:

   git clone https://github.com/your_username/solar-energy-prediction.git
   cd solar-energy-prediction
   pip install -r requirements.txt
   pip install pytest
   pytest
   

Built With 🦿

• Keras - High-level neural networks API for building and training deep learning models.
• Scikit-learn - Machine learning library for Python providing simple and efficient tools for data mining and data analysis.
• Matplotlib - Comprehensive library for creating static, animated, and interactive visualizations in Python.
• Seaborn - Python data visualization library based on Matplotlib, providing a high-level interface for drawing attractive statistical graphics.
• Pandas - Powerful data structures and data analysis tools for Python.
• NumPy - Fundamental package for scientific computing with Python.
• pytest - Framework for building simple and scalable test cases in Python.

Thank you for checking this out! Allah iysser ✨