Salary Prediction Using Machine Learning

This project aims to tackle the challenge of fair salary determination by developing a machine learning model for salary prediction.
Traditionally, setting salaries involves various subjective factors, leading to potential bias and inconsistencies.
This model provides an objective and data-driven approach to salary prediction based on job-related factors.

Motivation

Fair salary determination is crucial for promoting equity and inclusivity in the workplace.
Biased salary decisions can lead to dissatisfaction among employees and contribute to inequality within organizations.
By leveraging machine learning techniques, this project seeks to provide a fair and transparent method for salary prediction, mitigating the risks of bias and discrimination.

Scope

The model considers various job-related factors in predicting salaries, including:

• Education level
• Years of experience
• Job title
• Location
• Other relevant attributes

Fairness and Bias Mitigation

To address fairness and bias in salary prediction, the project implements techniques such as:

• Fair feature engineering
• Fairness-aware machine learning algorithms

Data Sources

The model is trained on data sourced from Kaggle.
Preprocessing steps are applied inside the program to ensure data quality and consistency, including data cleaning and normalization of the data.

Potential Impact

This project has the potential to:

• Improve transparency and fairness in salary determination processes.
• Empower organizations to make data-driven salary decisions.
• Promote equity in the workplace.

Usage

To use the salary prediction model, follow these steps:

1. Open a terminal or command prompt.

2. Navigate to the directory where your code files are located.

3. Make sure the dataset file is inside the same directory as your code file.

4. Install the required dependencies by running the following command:

   pip3 install -r requirements.txt
   
   

5. Run the script code.

6. Once the GUI is opened, enter the data input for the employee whose salary you want to predict.

7. After submitting, the predicted salary should pop up using two prediction models.

Contributing

Contributions to this project are welcome!
If you'd like to contribute, please follow these guidelines:

• Fork the repository.
• Create a new branch for your feature or bug fix.
• Commit your changes with descriptive commit messages.
• Submit a pull request to merge your changes into the main branch.

License

These isn't any license for this project and it's free to use.

Hope you guys find this project helpful for understanding and learning how to use AI models more deeply, as well as for practicing salary prediction and fairness in machine learning applications.