This project involved implementing a machine learning algorithm (gradient descent) for selecting the best parameters of a custom arctangent function to fit a curve of data.
It required deriving and experimenting with a variety of error functions, as well as implementing gradient descent from scratch, because the device the algorithm was meant to run on could not make use of sklearn.