This is the notes for the Spring 2019 Deep Learning course at NYU. This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional net and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition.

This is the initial draft of the course notes - they are based off of a course developed for the the African Masters of Machine Intelligence (AMMI). You can access that version here