SALES PREDICTION USING MULTIPLE LINEAR REGRESSION скачать в хорошем качестве

SALES PREDICTION USING MULTIPLE LINEAR REGRESSION

In this video, I explain my machine learning project where I built and optimized a Multiple Linear Regression model to predict sales based on advertising spend. The project includes: • Exploratory Data Analysis (EDA) • Correlation analysis • Model building and feature comparison • Train-test validation • Performance evaluation using RMSE and R² • Feature engineering using interaction terms • Model diagnostics using Yellowbrick After comparing multiple models, the final interaction model achieved an R² score of 0.978 on test data, demonstrating how the combined effect of TV and Radio advertising significantly influences sales. This project showcases how machine learning can be applied to optimize marketing strategies and support data-driven business decisions. If you want to add a small personal touch at the end, you can add: ✨ Thank you for watching!