Sales Prediction using Python

This repository contains the implementation for Task 4 of the CodeAlpha Data Science Internship.

Project Overview

The goal is to predict future product sales based on advertising expenditures across different channels (TV, Radio, and Newspaper) and evaluate marketing ROI.

Workflow & Methodology

1. Simulated marketing budget and sales distributions.
2. Built a Multiple Linear Regression model to identify advertising channel effectiveness.
3. Evaluated model accuracy using R² Score, MAE, and RMSE.
4. Analyzed channel coefficients to determine optimal ad spend allocation.

Key Insights

• Radio & TV Advertising: Showed the highest positive impact on driving sales volume.
• Model Performance: Achieved an R² Score of ~90%+.

How to Run

1. Install dependencies: pip install -r requirements.txt
2. Execute the script: python app.py