# 🔥 Algerian Forest Fire Prediction System 🌲
An end-to-end, **📱 phone-friendly** and responsive Machine Learning web application to predict the occurrence of forest fires in two regions of Algeria (**Bejaia** and **Sidi Bel-abbes**) based on meteorological variables.
---
## 📁 Project Structure
```text
algerian-forest-fire-prediction/
│── data/
│ ├── raw/ # 📂 Original dataset
│ └── processed/ # 🧹 Cleaned & scaled features
│── notebooks/ # 📓 Jupyter notebooks for EDA & prototyping
│── models/ # 💾 Pickled models, scalers, and evaluation metrics
│── src/ # ⚙️ Source code (preprocessing, training pipelines)
│── app.py # 🚀 Streamlit web application dashboard
│── requirements.txt # 📦 Python dependencies
│── Procfile # ☁️ Deployment config for Render/Heroku
│── README.md # 📖 Project documentation
```
---
## ⚙️ Setup & Local Installation
1️⃣ **Clone the repository**:
```bash
git clone
cd algerian-forest-fire-prediction
```
2️⃣ **Install dependencies**:
```bash
pip install -r requirements.txt
```
3️⃣ **Data Processing**:
Fetch the dataset and run the automated preprocessing pipeline:
```bash
python src/preprocess.py
```
4️⃣ **Model Training**:
Train multiple machine learning algorithms and automatically select and serialize the best performing model:
```bash
python src/train.py
```
5️⃣ **Run the Web Application**:
Launch the responsive Streamlit dashboard locally:
```bash
streamlit run app.py
```
---
## ✨ Key Features
- 📱 **Phone-friendly & Responsive UI**: Premium *"Dark Fire"* forest aesthetic with custom Streamlit styling, structured card layouts, and complete phone friendliness (optimized touch targets, scaling typography, and responsive margins across phones, tablets, and desktop displays).
- 📊 **Interactive Plotly Visualizations**: Features zoomable, interactive, and phone-friendly charts (stacked vertically with horizo …