💼 Salary Prediction Using Linear Regression

An interactive Machine Learning web application that predicts salary (in thousands) based on skill level using an explainable Linear Regression model.

Designed as a lightweight end-to-end ML project demonstrating model training, evaluation, visualization, and deployment using Streamlit and Hugging Face Spaces.

🚀 Live Demo

👉 https://huggingface.co/spaces/Siddhartha001/Salary_Prediction_Using_Linear_Regression

🧠 Project Overview

This project showcases a simple yet interpretable regression workflow:

Synthetic dataset for controlled experimentation

Linear Regression for salary prediction

Interactive user input using Streamlit

Real-time inference and visualization

Model performance metrics (MSE, R²)

The goal is to demonstrate core regression concepts, clean UI design, and reproducible ML deployment.

🛠 Tech Stack

Python

Streamlit

NumPy

Scikit-learn

Matplotlib

✨ Features

Interactive skill-level slider

Real-time salary prediction

Regression visualization with fitted line

Model evaluation metrics:

Mean Squared Error (MSE)

R² Score

Clean and explainable ML pipeline

📂 Project Structure Salary_Prediction_Using_Linear_Regression/ ├── src/ │ └── streamlit_app.py # Main Streamlit application ├── requirements.txt # Python dependencies ├── README.md # Project documentation

⚙️ How It Works

Synthetic skill vs salary data is generated

Linear Regression model is trained

User selects skill level through UI

Model predicts salary instantly

Visualization displays regression behavior

🌐 Deployment

Built using Streamlit

Hosted on Hugging Face Spaces

Automatic rebuild on commit

👨‍💻 Author

K. Siddhartha Python Developer | AI / NLP Developer

🔗 GitHub: https://github.com/k-siddhartha-ai

🤗 Hugging Face: https://huggingface.co/Siddhartha001

⭐ Notes

This project is intended for educational demonstration of regression modeling and explainable ML concepts. The dataset is synthetic and used for visualization purposes.