taher-software / ashrae---great-energy-predictor-iii

Develop accurate models for the global association Ashrae of metered building energy usage in the following areas: chilled water, electric, hot water, and steam meters. The data comes from over 1,000 buildings over a three-year timeframe.

Kaggle project : ASHRAE---Great-Energy-Predictor-III

This is my first contribution to kaggle competitions. In this competition, We are demanded to develop accurate models of metered building energy usage in the following areas: chilled water, electric, hot water, and steam meters. The data comes from over 1,000 buildings over a three-year timeframe. With better estimates of these energy-saving investments, large scale investors and financial institutions will be more inclined to invest in this area to enable progress in building efficiencies.

Built With 🔨

• Kaggle platform
• Python
• Keras
• Scikit-Learn
• Xgboost.

Live Demo

Live Demo Link

Install

To get a local copy up and running follow these simple example steps.

• Open terminal
• Clone this project by the command:

$ git clone [email protected]:Taher-web-dev/ASHRAE---Great-Energy-Predictor-III.git

• Then go to the main folder using the next command:

$ cd ASHRAE---Great-Energy-Predictor-III

Prerequisites

• IDE to edit and run the code (We use Jupyter Notebook 🔥).
• Git to versionning your work.

Usage

• Data scientist practioner
• For anyone interested by the topic of building energy consumption.

Authors

👤 Taher Haggui

• GitHub: @TaherHaggui
• LinkedIn: @TaherHaggui

🤝 Contributing

Contributions, issues, and feature requests are welcome!

Show your support

Give a ⭐️ if you like this project!

Acknowledgments

• kaggle plarform 💘 (https://www.kaggle.com/)
• My family's support 🙌

📝 License

This project is ASHRAE licensed.