Pytorch tutorial: Recurrent Neural Networks theory

Deep Learning DIY by Marc Lelarge https://twitter.com/marc_lelarge - slides: https://dataflowr.github.io/website/modules/11a-recurrent-neural-networks-theory/ 0:00 Recap 0:52 Introduction to RNNs 1:17 1D convolutional networks for sequences 2:16 Various tasks for RNNs 5:15 Theory of RNN 7:59 Backprop fro RNN 10:30 A binary classification problem for sequences 17:17 Elman network 21:02 Training RNN 22:51 Results for Elman network 24:22 Gating for RNN 28:10 Gated RNN in PyTorch 29:27 Results for gated RNN 30:12 LSTM and GRU 34:11 Equations for GRU 37:23 Equations for LSTM 40:31 LSTM in PyTorch 42:44 Results for LSTM 43:43 Empirical results for LSTM and GRU - full course: https://www.dataflowr.com/