Recurrent Neural Networks (RNNs)

Summary

Networks with loops that carry a hidden state across time steps, designed for sequential data like text and time series — the precursor to LSTMs and Transformers.

How to Learn This

1Implement a simple RNN for a sequence prediction task.
2Learn why plain RNNs struggle with long sequences (vanishing gradients).
3Understand the conceptual link between RNNs and how Transformers eventually replaced them.

Pooling Layers

LSTMs & GRUs

More topics in Deep Learning Architectures

Convolutional Neural Networks (CNNs)Pooling Layers LSTMs & GRUs Sequence-to-Sequence Models Attention Mechanism Transformer Architecture Positional Encoding Transfer Learning Autoencoders Generative Adversarial Networks (GANs, Overview)

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