This seminar will be held over Zoom. The link will be sent by your local Triangle seminar organiser or you can contact bogdan.stefanski.1@city.ac.uk for link. We propose machine learning inspired methods for computing numerical Calabi-Yau metrics, and implement them using Tensorflow/Keras. We compare them with previous work, and find that they are far more accurate for manifolds with little or no symmetry. We also discuss issues such as optimization methods, overparameterization and computational complexity. Joint work with Subramanian Lakshminarasimhan and Yidi Qi.