A project obtained rank 139/709 of Women in Data Science Datathon 2023 using CatBoost and LightGBM to forecast sub-seasonal temperatures ((temperatures over a two-week period) within the United States.
This model using a pre-prepared dataset consisting of weather and climate information for a number of US locations, for a number of start dates for the two-week observation, as well as the forecasted temperature and precipitation from a number of weather forecast models. (Environment: GPU T4 x2)
Source for more clarification: https://www.kaggle.com/kimnganngng/competitions?tab=completed
Datathon source: https://www.kaggle.com/competitions/widsdatathon2023
Data source: https://www.kaggle.com/competitions/widsdatathon2023/data