ndeyekwade-cmd/Machine-Learning-AIMS

Air Quality Analysis using Machine Learning - AIMS Senegal Academic Project # Machine Learning - Air Quality Analysis **AIMS Senegal Academic Project** *Master's in Mathematical Sciences with Big Data Specialization* --- ## 📋 Project Overview This project focuses on **air quality prediction and analysis** using machine learning techniques. The goal is to predict air quality levels based on environmental and temporal factors, providing actionable insights for public health and environmental monitoring. ### Team Members - **Ndeye Khady Wade** - Group 8 Members ### Supervisor Dr. Yae Olatoundji Ulrich Gaba (AIMS RIC, Rwanda) --- ## 🎯 Objectives 1. Analyze air quality data to identify patterns and trends 2. Build predictive models for air quality classification 3. Evaluate and compare different machine learning algorithms 4. Provide insights for environmental decision-making --- ## 📊 Dataset The dataset includes various environmental parameters: - Temporal features (date, time) - Environmental measurements - Air quality indicators - Classification labels (Good, Moderate, Poor, etc.) --- ## 🔬 Methodology ### 1. Data Preprocessing - Data cleaning and handling missing values - Feature engineering and extraction - Data normalization and standardization - Train-test split ### 2. Machine Learning Models Implemented - **Classification Algorithms:** - Logistic Regression - Decision Trees - Random Forest - Support Vector Machines (SVM) - K-Nearest Neighbors (KNN) - Gradient Boosting ### 3. Model Evaluation - Accuracy, Precision, Recall, F1-Score - Confusion Matrix Analysis - Cross-validation - Feature importance analysis --- ## 📈 Key Results The models were evaluated and compared based on multiple performance metrics. The analysis revealed: - Strong predictive performance across multiple algorithms - Key environmental factors influencing air quality - Temporal patterns in air quality variations *Detailed results are available in the presentation PDF and Jupyter notebook.* --- ## 🛠️ Technologies Used - **Python 3.x** - **Libraries …