SalaryPredictor

Predicts salaries based on years of experience, test scores, and interview scores using an AI model.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Contributing
• License
• Contact

Introduction

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.

Features

• 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

Installation

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

Usage

1. Clone the repository

git clone https://github.com/salihfurkaan/SalaryPredictor.git
cd SalaryPredictor

2. 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($)

3. Run the notebook.

4. Interpret the results printed by the model for the given input values.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any changes.

License

This project is licensed under the MIT License.

Contact

For any questions or inquiries, please contact [email protected]