Salary Prediction Web App

Overview

This web application predicts a salary based on the number of years of experience using a linear regression model. The application is built using Flask, a Python web framework.

Prerequisites

Before using the Salary Prediction web application, ensure you have the following installed:

• Python (3.6 or higher)
• Flask
• scikit-learn
• pandas

Installation

1. Clone the repository:

   git clone https://github.com/Alwin-Sajan/Salary_Prediction_ML.git

2. Navigate to the project directory:

   cd Salary_Prediction_ML

3. Install dependencies:

   pip install -r requirements.txt

Usage

1. Run the Flask application:

   python app.py

2. Open your web browser and go to http://127.0.0.1:5000/.

3. Enter the number of years of experience and click the "Predict Salary" button.

File Structure

• app.py: The main Flask application file.
• templates/index.html: HTML template for the web page.
• Salary_data.csv: Dataset containing information about years of experience and corresponding salaries.

Dependencies

The following Python libraries are used in this project:

• Flask: Web application framework.
• pandas: Data manipulation library.
• scikit-learn: Machine learning library for linear regression.

Additional Notes

• The linear regression model is trained on the provided dataset (Salary_data.csv).
• This application is for educational purposes, and additional considerations are needed for a production environment.

Future Improvements

• Implement user authentication and authorization.
• Improve the front-end for a more user-friendly experience.
• Enhance error handling and input validation.
• Consider deploying the application to a production server.