MAJOR PROJECT " SALES REVENUE PREDICTION USING MULTIPLE LINEAR REGRRSSION"

Описание: In this video, I present my major project on Sales Revenue Prediction using Multiple Linear Regression.

The objective of this project is to analyze how advertising investments across different media channels influence product sales and to develop a predictive model that estimates sales revenue based on marketing expenditure.

The study is based on the Advertising dataset, which includes advertising budgets across:

• TV
• Radio
• Newspaper

This project covers the complete data science workflow, including:

✔ Data understanding and preprocessing
✔ Exploratory Data Analysis (EDA)
✔ Correlation analysis
✔ Multiple Linear Regression modeling
✔ Feature selection and model comparison
✔ Train-test validation
✔ Model diagnostics
✔ Interaction effect (TV & Radio synergy analysis)

Key Insights:

• TV and Radio advertising significantly impact Sales
• Newspaper has limited predictive contribution
• Feature selection improves model efficiency
• Interaction between TV and Radio enhances prediction performance

This project demonstrates how statistical modeling and machine learning can support data-driven marketing decisions and optimize advertising budget allocation.

🛠 Tools & Technologies Used:

Python | Pandas | NumPy | Seaborn | Matplotlib | Scikit-learn | Yellowbrick

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