Predicts salaries based on years of experience, test scores, and interview scores using an AI model.
This project includes an AI model that estimates the salaries of individuals based on their years of experience, test scores, and interview scores. The model is built using a linear regression algorithm.
- Predicts salary for different experience levels and scores
- Handles missing values in the dataset
- Provides visualizations for data exploration and correlation
- Easy to use with simple input parameters
- Includes examples and usage instructions
To run this project, you need to have Python and the following libraries installed:
- pandas
- seaborn
- scikit-learn
- word2number
- numpy
- matplotlib
You can install the required libraries using the following commands:
pip install pandas seaborn scikit-learn matplotlib word2number- Clone the repository
git clone https://github.com/salihfurkaan/SalaryPredictor.git
cd SalaryPredictor-
Prepare your dataset in the same format as
hiring.csv: Columns should include experience, test_score(out of 10), interview_score(out of 10), and salary($) -
Run the notebook.
-
Interpret the results printed by the model for the given input values.
Contributions are welcome! Please open an issue or submit a pull request for any changes.
This project is licensed under the MIT License.
For any questions or inquiries, please contact [email protected]