NYU Deep Learning SP21 - 01L – Gradient descent and the backpropagation algorithm

Course website: http://bit.ly/DLSP21-web Playlist: http://bit.ly/DLSP21-YouTube Speaker: Yann LeCun Chapters 00:00:00 – Supervised learning 00:03:43 – Parametrised models 00:07:23 – Block diagram 00:08:55 – Loss function, average loss 00:12:23 – Gradient descent 00:30:47 – Traditional neural nets 00:35:07 – Backprop through a non-linear function 00:40:41 – Backprop through a weighted sum 00:50:55 – PyTorch implementation 00:57:18 – Backprop through a functional module 01:05:08 – Backprop through a functional module 01:12:15 – Backprop in practice 01:33:15 – Learning representations 01:42:14 – Shallow networks are universal approximators! 01:47:25 – Multilayer architectures == compositional structure of data