/Predict-Sales-Revenue-Using-Multiple-Regression-Model

In this project you will build and evaluate multiple linear regression models using Python. You will use scikit-learn to calculate the regression, while using pandas for data management and seaborn for data visualization. The data for this project consists of the very popular Advertising dataset to predict sales revenue based on advertising spending through media such as TV, radio, and newspaper.

Primary LanguageJupyter Notebook

Predict Sales Revenue Using Multiple Regression Model

Description:-

In this project ,I have built and evaluated multiple linear regression models using Python. I have used scikit-learn to calculate the regression, while using pandas for data management and seaborn for data visualization. The dataset for this project consists of the very popular Advertising dataset to predict sales revenue based on advertising spending through media such as TV, radio, and newspaper.

Key Task :

  • Built univariate and multivariate linear regression models using scikit-learn .
  • Performed Exploratory Data Analysis (EDA) and data visualization with seaborn .
  • Evaluated model fit and accuracy using numerical measures such as R² and RMSE .
  • Performed Model interaction effects in regression using basic feature engineering techniques.
  1. Notebook Link

  2. Dataset Link