ADEYEMIBolaji/african-foodstore-anomaly
Domain:
socioeconomicRecord type:
softwareproject
Creator:
ADE
Host:
# 🛒 African Foodstore Anomaly Detection App 🇬🇧🌍
This project builds a real-time anomaly detection system for a typical African Food Store's e-commerce data in the UK.
It covers everything from data generation, model training, to a live Streamlit web app where users can upload their transactions and detect anomalies.
---
## 🚀 Project Overview
**Features:**
- Generate synthetic African food e-commerce transactions
- Train and compare three anomaly detection models:
- Isolation Forest
- AutoEncoder (Deep Learning)
- One-Class SVM
- Select and save the best performing model
- Deploy a Streamlit app for real-time anomaly detection
- Allow users to upload CSV files and download detected results
---
## 🌐 Live Demo
You can try the deployed app here:
👉 African Foodstore Anomaly Detection App
---
## 🏗 Project Structure
```bash
african-foodstore-anomaly/
├── app.py # Streamlit frontend
├── data/ # Synthetic dataset and test data
│ ├── ecommerce_data.csv
│ ├── test_data.csv
│ └── generate_data.py
├── models/ # Model training and saved models
│ ├── train_models.py
│ ├── best_model.pkl or best_model.h5
│ ├── scaler.pkl
├── notebooks/ # EDA and preprocessing notebooks
│ ├── eda_preprocessing.ipynb
│ └── model_training.ipynb
├── requirements.txt # Project dependencies
├── README.md # Project documentation
└── .gitignore
```
---
## 📦 Tech Stack
- **Python 3.12**
- **Streamlit**
- **Scikit-learn**
- **Tensorflow / Keras**
- **Pandas / Numpy**
- **Matplotlib / Seaborn**
- **Joblib**
---
## 🛠 How to Run the Project Locally
1. **Clone the repository:**
```bash
git clone github.com
cd african-foodstore-anomaly
```
2. **Create a virtual environment (optional but recommended):**
```bash
python -m venv venv
source venv/bin/activate # On Mac/Linux
venv\Scripts\activate # On Windows
```
3. **Install dependencies …