This project predicts future sales trends using historical sales data and Machine Learning techniques. It was developed as part of the Future Interns Machine Learning Internship Program.
- Analyze historical sales data
- Perform data cleaning and preprocessing
- Create time-based features
- Forecast future sales using Linear Regression
- Visualize trends and predictions
- Generate business insights for decision-making
- Python
- Pandas
- NumPy
- Matplotlib
- Scikit-Learn
Sample Superstore Dataset
- Data Cleaning
- Feature Engineering
- Monthly Sales Analysis
- Category-wise Sales Analysis
- Sales Forecasting
- Model Evaluation (MAE, RMSE, R²)
- Actual vs Predicted Comparison
- Future Sales Forecast Visualization
- monthly_sales.png
- category_sales.png
- actual_vs_predicted.png
- sales_forecast.png
- Inventory Planning
- Demand Forecasting
- Budget Optimization
- Staffing Decisions
- Data-Driven Business Insights
The project demonstrates how Machine Learning can be used to forecast future sales and support business decision-making through predictive analytics and visualization.