Olayimka/Weather-Prediction-Forecast

Machine Learning model for analyzing and predicting long-term weather patterns in Nigeria # Weather-Prediction-Forecast Machine Learning model for analyzing and predicting long-term weather patterns in Nigeria ## 📊 Dataset The dataset used in this project consists of historical weather data collected over a period of time. It includes key meteorological features required for analyzing and predicting long-term weather patterns. Features: - Temperature (°C) - Humidity (%) - Wind Speed (km/h or m/s) - Atmospheric Pressure (hPa) - Precipitation (mm) - Date/Time (timestamp) The dataset was obtained from publicly available weather data sources and represents time-series data, where each observation corresponds to a specific time interval. Data Characteristics: - Structured time-series dataset - Contains both seasonal and trend components - May include missing or noisy values, which were handled during preprocessing Usage in Project: The dataset is used to train machine learning models to: - Identify patterns in historical weather conditions - Predict future temperature and weather trends - Analyze long-term climate behavior Data preprocessing steps such as normalization, handling missing values, and sequence generation were applied before feeding the data into the model.