Machine Learning and Statistical Models for Time Series Climate Prediction

This github will be updated periodically.

Description

This repository contains Machine Learning & Statistical models to predict climate variables (maximum temperature, minimum temperature, humidity and rain) using methods like ARIMA, Holt-Winters, Random Forest, LSTM, and XGBoost.

Data

The processed data includes 10 daily years (2013 - 2023) and 37 monthly years (1986-2023). The varaibles used to study and predict are located in the district of Zurite, province of Anta in Cusco - Peru.

• Maximum temperature
• Minimum temperature
• Humidity
• Rain