This project is an exploration of time series forecasting using SARIMA (Seasonal AutoRegressive Integrated Moving Average) models and Random Forest regression applied to weather data for Anchorage Alaska. The goal is to predict weekly maximum temperatures based on historical weather data.
The project is divided into three Jupyter notebook files:
- Data Preparation: Acquiring and preprocessing weather data from the National Oceanic and Atmospheric Administration (NOAA).
- SARIMA Modeling: Implementing a SARIMA model to predict maximum temperatures.
- Random Forest Modeling: Using a Random Forest regressor for prediction and comparing its performance with SARIMA.