This project aims to train and test machine learning models for correcting the telescope pointing. It consists of two main experiments: training and testing.
In this experiment, the data is split into 6 folds. For each fold, the data is further divided into training, validation, and a consecutive test set.
In this experiment, the data is split into 6 folds. One fold is used for testing, while the remaining 5 folds are used for training and validation. This process is repeated for all six folds to evaluate the performance of the models in a cross-fold manner.
This project is licensed under the MIT License.