Long Short-Term Memory Networks

This lecture covers the challenges of vanishing and exploding gradients in recurrent neural networks (RNNs) and introduces Long Short-Term Memory (LSTM) networks as a solution. It explains the architecture of LSTMs, including the concept of cell states, gates, and memory management. The lecture also discusses bidirectional RNNs and multi-layer RNNs, highlighting their benefits and practical considerations. Additionally, it explores the impact of LSTMs on various NLP tasks and compares them with other neural network architectures.