This project was done as a part of the Applied Machine Learning Course (COMP 551) at McGill University and was done in a group of 3 students. Ospreys are severely affected by pollutants in their environment because they are at the top of their food chain. The population of ospreys in the eastern USA significantly decreased due to DDT use in the middle of the twentieth century. It has since recovered. This project dealt with the basic methodology and results obtained for an osprey data set chosen from Movebank for predicting the migration periodicity and directionality exhibited by these birds as a group and individually. K-means clustering and the Discrete Fourier Transform were used to predict the migration patterns. Long Short-Term Memory was used to predict the future movement of the birds. This analysis could help identify unusual patterns in bird migration trajectories in the future. If unusual patterns present themselves among many birds, the possible pollutant needs to be identified and eliminated from the region. I helped in data extraction and implemented k-means clustering algorithm.