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Lecture
Recurrent Neural Networks: LSTMs & GRUs
Description
This lecture covers the continuation of recurrent neural networks with multiple layers and bidirectionality, focusing on LSTM and GRU variants. It discusses the challenges of learning long-range dependencies, the use of gates in GRUs, and the advantages of LSTMs and GRUs over traditional RNNs. The instructor explains the concepts through practical examples and addresses issues like vanishing gradients and optimal architectures for different tasks.
Official source
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