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The Machine Learning Telescope Pointing Correction code trains and tests machine learning models for correcting telescope pointing. Using historical APEX data from 2022, including pointing corrections, and other data such as weather conditions, position and rotation of the secondary mirror, pointing offsets observed during pointing scans, and the position of the sun, among other data, the code treats the data in two different ways to test which factors are the most likely to account for pointing errors.