Hitesh-Harsh/Algerian-Forest-Fire-Analysis

In this project, I have done EDA(in Python), Model Creation and Model Evaluation and Created a Pickle File for Deployment. **Algerian Forest Fire Analysis and ML Model Optimization** **Project Overview** **Objective:** Conducted a comprehensive analysis of forest fires in Algeria and optimized machine learning models using hyperparameter tuning. **Data Preprocessing and Transformation** Transformed data from rows to columns based on specific parameters. Removed multicollinearity to enhance model performance. Optimized data types to reduce memory usage and improve processing speed. Dropped unnecessary columns according to the problem statement. Corrected spelling errors in the dataset. Plotted histograms to understand data distribution and identify/remove outliers. **Exploratory Data Analysis (EDA)** Analyzed fire points across different regions to identify patterns and trends. Used visualizations to gain insights into the frequency and severity of fires. Model Implementation and Evaluation **Implemented multiple regression models using the Scikit-learn library:** Linear Regression: Baseline model to establish initial performance. Ridge Regression: Improved accuracy and reduced overfitting; selected as the best-performing model. Lasso Regression: Evaluated for feature selection and sparsity. ElasticNet Regression: Combined Lasso and Ridge to balance bias and variance. Conducted hyperparameter tuning to optimize model performance. Achieved significant accuracy improvements through model evaluation and selection. **Model Deployment** Created a pickle file for the optimized Ridge Regression model to facilitate easy deployment and use in real-time applications. **Tools and Technologies Used** **Programming Languages:** Python **Libraries:** Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn **Techniques:** Hyperparameter Tuning, Data Cleaning, Feature Engineering, Model Evaluation **Deployment:** Pickle for model serialization and deployment **Key Achievements** Enhanced model accuracy through rigorous data preprocessing and hyperparameter optimization. Successfully identifi …