💼 Salary Prediction Model

This project demonstrates a simple Linear Regression model built with scikit-learn to predict a person's salary based on their years of experience. The model is deployed using Streamlit for a clean and interactive web interface.

🌐 Live Demo

🔗 Visit Website

📸 Screenshot

📊 Dataset

• Source: Salary Dataset
• Contains:
  • Experience Years
  • Salary

🔧 Technologies Used

• Python
• Pandas & Matplotlib
• Scikit-learn
• Streamlit
• Pickle (for model serialization)

🧠 Model Workflow

1. Load Dataset (online & offline options)
2. Visualize the relationship using a scatter plot
3. Split data into training and testing sets
4. Train a Linear Regression model
5. Evaluate model with R² Score and MSE
6. Serialize the trained model using pickle
7. Deploy using Streamlit

🙏 Contributors

Thanks to everyone who’s contributed!

• Mubeen Channa (@Mubeen-Channa) – Project Maintainer
• Irfan Narejo (@meet-irfan) – Boosted accuracy to 90% (+4%) and reduced MSE from 48 to 31
• Muhammad Younis (@YounisJ) – Updated salary dataset with new experience and compensation entries

Feel free to add yourself here if you make a contribution!

Mubeen Channa Project Lead & Maintainer — Designed, built, and deployed the model

Irfan Narejo Boosted accuracy to 90% (+4%) and reduced MSE from 48 to 31

Muhammad Younis Updated salary dataset with new experience and compensation entries

🚀 How to Run Locally

1. Clone the repository
2. Install required packages:

   1. pip install pandas matplotlib scikit-learn streamlit
   2. python -m streamlit run app.py / streamlit run app.py