# 🌲 Algerian Forest Fires Prediction
This repository contains an **end-to-end machine learning project** using the **Algerian Forest Fires dataset**. The goal is to predict whether a fire occurs based on meteorological conditions using various supervised ML models.
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## 📌 Repository Structure
- `2.0-EDA And FE Algerian Forest Fires.ipynb` → Exploratory Data Analysis (EDA) & Feature Engineering
- `3.0-Model Training.ipynb` → Model training, evaluation, and saving artifacts
- `Algerian_forest_fires_cleaned_dataset.csv` → Cleaned dataset after preprocessing
- `Algerian_forest_fires_dataset_UPDATE.csv` → Updated dataset used for training
- `ridge.pkl` → Saved Ridge Regression model
- `scaler.pkl` → Saved StandardScaler object
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## 🔎 Project Workflow
1. **Data Preprocessing & Cleaning**
- Handling missing values and formatting issues
- Preparing datasets for modeling
2. **Exploratory Data Analysis (EDA)**
- Statistical summaries and visualization
- Correlation analysis of meteorological features
3. **Feature Engineering**
- Scaling numerical features
- Encoding categorical variables
4. **Model Training**
- Ridge Regression and other ML algorithms
- Hyperparameter tuning
- Saving trained models as `.pkl`
5. **Model Evaluation**
- Metrics: Accuracy, Precision, Recall, F1-score
- Visualizations: confusion matrix, ROC-AUC
6. **Deployment Ready Artifacts**
- Exported model (`ridge.pkl`)
- Exported scaler (`scaler.pkl`)
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## ⚙️ Installation
Clone the repo and install dependencies:
```bash
git clone
github.com
cd algerian-forest-fires-prediction
pip install -r requirements.txt