https://github.com/yuvrajsaraogi/sales-prediction-using-python
Sales prediction involves estimating future product sales based on factors like advertising spend, target audience, and platform. Businesses rely on data scientists to forecast sales and optimize advertising costs. Machine learning in Python can be used for this task.
https://github.com/yuvrajsaraogi/sales-prediction-using-python
data data-analysis data-science data-visualization machine-learning matplotlib natural-language-processing numpy pandas prediction python sales-prediction-using-python sql
Last synced: about 2 months ago
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Sales prediction involves estimating future product sales based on factors like advertising spend, target audience, and platform. Businesses rely on data scientists to forecast sales and optimize advertising costs. Machine learning in Python can be used for this task.
- Host: GitHub
- URL: https://github.com/yuvrajsaraogi/sales-prediction-using-python
- Owner: yuvrajsaraogi
- Created: 2025-03-15T17:48:44.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-16T18:30:00.000Z (about 1 year ago)
- Last Synced: 2025-04-06T07:40:46.085Z (about 1 year ago)
- Topics: data, data-analysis, data-science, data-visualization, machine-learning, matplotlib, natural-language-processing, numpy, pandas, prediction, python, sales-prediction-using-python, sql
- Language: Jupyter Notebook
- Homepage:
- Size: 403 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊 Sales Prediction using Python
## 📌 Project Overview
This project predicts **sales revenue** based on **advertising budgets** using **machine learning**. The dataset includes advertising expenditures on **TV, Radio, and Newspaper**, and the goal is to build a model to predict sales based on these investments.
## 🗂 Dataset Overview
The dataset consists of **200 entries** with the following columns:
- `TV` – Advertising budget for TV (in $1000s)
- `Radio` – Advertising budget for Radio (in $1000s)
- `Newspaper` – Advertising budget for Newspaper (in $1000s)
- `Sales` – Sales revenue generated (in $1000s) (Target variable)
## ⚙️ Technologies Used
- Python 🐍
- Pandas & NumPy (Data Processing)
- Matplotlib & Seaborn (Data Visualization)
- Scikit-learn (Machine Learning – Linear Regression)
## 🚀 Features
✅ Data Cleaning and Preprocessing
✅ Exploratory Data Analysis (EDA)
✅ Sales Prediction using **Linear Regression**
✅ Model Evaluation Metrics
## 🔥 Usage
- **Load and explore the dataset.**
- **Perform Exploratory Data Analysis (EDA)** to visualize trends in advertising and sales.
- **Train a Linear Regression model** to predict sales.
- **Evaluate the model's performance** using:
- **R² Score**
- **Mean Squared Error (MSE)**
## 📊 Visualizations
The notebook includes:
✅ **Pairplots** for feature relationships
✅ **Correlation Heatmap** to find important variables
✅ **Regression Plot** to visualize predictions
## 🤝 Contributing
Contributions are welcome! 🎉
If you’d like to contribute, please:
- **Fork the repository**
- **Create a new branch (`feature-branch`)**
- **Submit a pull request**
## 📜 License
This project is licensed under the **MIT License**.