asheeransari/ML_Project_Algerian_Forest_Fire_Prediction_LinearRegression

## ML_Project_LinearRegression ## Project Info This Machine Learning Project Predict the Fire Weather Index with the help of other features present in Algerian Forest Fire Dataset. This is the simple Machine Learning Project that use Linear Regression Algorithm to predict the output. ## Requirments 1 - Jupyter Notebook 2 - VS-Code 3 - kaggle 4 - Git 5 - GitHub # List of Libraries that is used in this project 1 - numpy 2 - pandas 3 - matplotlib 4 - seaborn 5 - scikit-learn 6 - flask 7 - jinja2 ## Dataset Info - Additional Information The dataset includes 244 instances that regroup a data of two regions of Algeria,namely the Bejaia region located in the northeast of Algeria and the Sidi Bel-abbes region located in the northwest of Algeria. - 122 instances for each region. The period from June 2012 to September 2012. The dataset includes 11 attribues and 1 output attribue (class) The 244 instances have been classified into ‘fire’ (138 classes) and ‘not fire’ (106 classes) classes. - Dataset Link - Algerian Forest Fires Datas… ## Steps used in this project 1- Collecting Data 2- Cleaning and Preparing the Data 3 - Exploring the Data (EDA) 4 - Visualize the Data 5 - Analyzing the Data 6 - Feature Engineering 7 - Training and Evaluating the Model 8 - Model Training 9 - Model Optimization 10 - Deployment