AI Terms Dictionary

Definition

LSTM networks address the vanishing gradient problem common in standard RNNs by using a cell state and three gating mechanisms: input, forget, and output gates. These gates regulate the flow of information, allowing the network to remember important details over long sequences and forget irrelevant ones. This architecture is particularly effective for tasks involving time-series prediction, natural language processing, and speech recognition where context duration matters.

Summary

A specialized recurrent neural network architecture designed to learn long-term dependencies in sequential data.

Key Concepts

• Gating Mechanisms
• Cell State
• Sequential Data
• Vanishing Gradient

Use Cases

• Time series forecasting
• Speech recognition
• Machine translation

Code Example

1
2

import torch.nn as nn
lstm = nn.LSTM(input_size=10, hidden_size=20, num_layers=1)

Related Terms

• recurrent_neural_network
• gates
• sequence_modeling
• nlp