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Deep Learning / 15

RNNs, LSTMs & GRUs

Work through recurrent networks, backpropagation through time, LSTM gates, and GRUs.

Section 15 of 32 · 18 subtopics

This is a knowledge index. Published titles open their articles; the remaining entries outline planned coverage.

RNN

  1. 15.01

    Recurrent Neural Networks

    Planned guide: Recurrent Neural Networks. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  2. 15.02

    Hidden State

    Planned guide: Hidden State. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  3. 15.03

    Recurrent Connections

    Planned guide: Recurrent Connections. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  4. 15.04

    Backpropagation Through Time

    Planned guide: Backpropagation Through Time. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  5. 15.05

    Vanishing Gradients in RNNs

    Planned guide: Vanishing Gradients in RNNs. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  6. 15.06

    Exploding Gradients in RNNs

    Planned guide: Exploding Gradients in RNNs. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation

LSTM

  1. 15.07

    LSTM

    Planned guide: LSTM. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  2. 15.08

    Cell State

    Planned guide: Cell State. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  3. 15.09

    Forget Gate

    Planned guide: Forget Gate. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  4. 15.10

    Input Gate

    Planned guide: Input Gate. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  5. 15.11

    Output Gate

    Planned guide: Output Gate. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation

GRU

  1. 15.12

    GRU

    Planned guide: GRU. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  2. 15.13

    Update Gate

    Planned guide: Update Gate. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  3. 15.14

    Reset Gate

    Planned guide: Reset Gate. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  4. 15.15

    LSTM vs GRU

    Planned guide: LSTM vs GRU. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation

Advanced

  1. 15.16

    Bidirectional RNN

    Planned guide: Bidirectional RNN. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  2. 15.17

    Stacked RNN

    Planned guide: Stacked RNN. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation
  3. 15.18

    Encoder-Decoder RNN

    Planned guide: Encoder-Decoder RNN. Focus on intuition, assumptions, and a worked example.

    intermediateArticle in preparation