This project predicts the salary of data science professionals based on various job-related features using a machine learning model. It includes a web app built using Streamlit, trained and deployed through Google Colab.
- Predicts salary in USD based on job details
- Handles categorical encoding using LabelEncoder
- Uses models use Gradient Boosting Regressor
- Streamlit interface for interactive user input
- Visualizations matplotlib
- Saved model and encoders using joblib
- Encode categorical variables using `LabelEncoder`
- Split dataset into training and testing sets
- Trained using `GradientBoostingRegressor`
- Metrics: MAE, RMSE, R² Score
- Feature importance visualization
- MAE: 957.4296786173261
- RMSE: 4431.804635661977
- R² Score: 0.996337643891413