Knowledge Graph — Coursera Notes › Academic disciplines › Information Technology / Computer Science › Artificial Intelligence › Deep Learning

LSTM

concept · part of Deep Learning

A variant of RNN that captures long-term dependencies in sequences. LSTM is an advanced RNN architecture that addresses long-term dependencies by maintaining a cell state and gates, making it effective for capturing information over long sequences.

LSTMs use memory cells and three gates (input, forget, output) to control information flow, deciding what to retain or discard. They are effective for language processing, time-series forecasting, and sequential data analysis where context over time is critical. They are used in advanced sentiment analysis systems.

Connections

This is the text view of an interactive 3D knowledge graph — open this page with JavaScript enabled to explore it visually.

🧠 Knowledge Graph

Select a node

The owner's editing tools — shown here so you can see how the graph is grown, but read-only.

Click a bubble to drill in · click again to collapse · drag to move around