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. The prerequisites include: DS-GA 1001 Intro to Data Science or a graduate-level machine learning course.
**Joan Bruna (JB), Yann LeCun (YLC), and Alfredo Canziani (AC)**
Jiuhong Xiao [email protected], Rahul Ahuja [email protected], Ayesha Ahmed [email protected], Rohith Mukku [email protected]