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.
- Kaggle platform
- Python
- Keras
- Scikit-Learn
- Xgboost.
To get a local copy up and running follow these simple example steps.
- Open terminal
- Clone this project by the command:
$ git clone git@github.com: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
- IDE to edit and run the code (We use Jupyter Notebook 🔥).
- Git to versionning your work.
- Data scientist practioner
- For anyone interested by the topic of building energy consumption.
👤 Taher Haggui
- GitHub: @TaherHaggui
- LinkedIn: @TaherHaggui
Contributions, issues, and feature requests are welcome!
Give a ⭐️ if you like this project!
- kaggle plarform 💘 (https://www.kaggle.com/)
- My family's support 🙌
This project is ASHRAE licensed.