Neural Nets for NLP 2021 - Recurrent Neural Networks

Neural Nets for NLP 2021 - Recurrent Neural Networks

Explore recurrent neural networks for natural language processing in this comprehensive lecture from CMU's Neural Networks for NLP course. Dive into topics including bi-directional recurrent networks, vanishing gradients, LSTMs, and the strengths and weaknesses of recurrence in sentence modeling. Learn about parameter tying, mini-batching techniques, and optimized LSTM implementations. Discover how to handle long-distance dependencies and long sequences in language processing tasks. Gain insights into pre-training methods for RNNs and explore advanced concepts like gated recurrent units and soft hierarchical structures.