Advert Sales Prediction

This repository contains a simple Python script for predicting sales based on advertising data using linear regression. The script uses the scikit-learn library for machine learning and seaborn and matplotlib for data visualization.

Getting Started

Advert Sales Prediction

This repository contains a simple Python script for predicting sales based on advertising data using linear regression. The script uses the scikit-learn library for machine learning and seaborn and matplotlib for data visualization.

Getting Started

Prerequisites

Make sure you have the following libraries installed:

pandas numpy seaborn matplotlib scikit-learn

You can install them using the following command:

pip install pandas numpy seaborn matplotlib scikit-learn

Data

The project uses a CSV file named "Advert.csv" for the dataset. Ensure that the file is present in the same directory as the script.

Results

The script will output the Mean Squared Error and R-Squared values, providing insights into the accuracy of the linear regression model in predicting sales based on advertising features.

Feel free to modify and experiment with the script to enhance your understanding or adapt it for your specific needs.