DS Salary Prediction using Polynomial Regression

This project focuses on predicting data science salaries based on experience using Polynomial Regression. The dataset contains job-related details, including years of experience and corresponding salaries.

📊 Project Overview

• Goal: Predict salaries in the data science field using machine learning.
• Algorithm: Polynomial Regression (Scikit-learn)
• Dataset: Synthetic or real-world salary data with experience as the main feature.
• Language: Python

🧰 Technologies Used

• Python
• NumPy
• Pandas
• Matplotlib
• Scikit-learn

📁 Files in this Repository

• DS_Salary_Prediction_Polynomial.ipynb – Jupyter Notebook with code and visualization.
• Position_Salaries.csv – Dataset used for training the model.
• README.md – Project documentation.

🔍 Key Features

• Data loading and exploration
• Polynomial feature transformation
• Model training and prediction
• Visualization of regression curve
• Model comparison (Linear vs Polynomial)