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Stop 09 · Deep Learning FundamentalsTopics · 7/10

Recurrent Neural Networks (RNNs) & LSTMs

Part of the Data Science Roadmap

In short

Architectures designed for sequential data (text, time series) that maintain a 'memory' of previous inputs — LSTMs specifically solve RNNs' tendency to forget long-range dependencies.

How to learn this

  1. 1Read a conceptual explanation of why sequence order matters for these architectures.
  2. 2Build a simple LSTM for a basic sequence prediction task.
  3. 3Learn why Transformers (Phase 10) have largely replaced RNNs/LSTMs for most NLP tasks today.

More topics at this stop

Neural Network BasicsActivation FunctionsBackpropagation & Gradient DescentBuilding Networks With TensorFlow / KerasBuilding Networks With PyTorchConvolutional Neural Networks (CNNs)Transfer LearningRegularization in Deep Learning (Dropout, Batch Norm)GPUs & Training Basics

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