This project aims to predict video game sales based on various features such as genre, platform, and region. The dataset used for this project is in CSV format and contains information about over 16,000 video games.
- Clone the repository:
git clone https://github.com/your_username/video-game-sales-prediction.git
- Install the required packages:
pip install -r requirements.txt
- Start Jupyter Notebook:
jupyter notebook
- Open
games_sales_prediction.ipynb
in the browser. - Follow the instructions in the notebook to run the project.
The dataset used for this project is included in the repository as Video_Games.csv
. It contains the following columns:
- Name: the name of the game
- Platform: the platform on which the game is released
- Year: the year of the game's release
- Genre: the genre of the game
- Publisher: the publisher of the game
- NA_Sales: sales in North America (in millions)
- EU_Sales: sales in Europe (in millions)
- JP_Sales: sales in Japan (in millions)
- Other_Sales: sales in other regions (in millions)
- Global_Sales: total worldwide sales (in millions)
This project is licensed under the MIT License. See the LICENSE
file for details.