Term · Topic

Recurrent Neural Network (RNN)

Q: What is Recurrent Neural Network?

Recurrent Neural Network (RNN) is a Neural Network (NN) architecture that processes sequential data by maintaining a state that captures information from previous time steps and uses that state, together with current inputs, to produce outputs and updated states. Expanded Explanation 1. Technical Function and Core Characteristics Recurrent Neural Networks (RNNs) use cyclic connections so that the output from one step feeds into the network as input for the next step together with new data. This

Recurrent neural network is a neural network architecture for modeling sequential data that maintains an internal state over time, enabling enterprises to process and learn from ordered inputs such as text, speech, logs, or time-series signals for analytic and automation use cases.

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curl -X POST https://mcp.decisioninsights.ai/api/mcp-public \
  -H "content-type: application/json" \
  -H "accept: application/json, text/event-stream" \
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REST

GET https://api.decisioninsights.ai/api/public/v1/glossary/5ea3a58d-0f3b-4b6c-b93a-a31e252ae43f

CLI

di get-glossary --slug recurrent-neural-network-rnn

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How an agent can rely on this definition

What the record lets an agent check before it uses the term in an answer.

The check	What the record shows	Where it is in the data
It's a known term	One entry, with its abbreviation and type (topic)	`name, alternateName`
It sits in a glossary	Linked to Recurrent Neural Networks, Long Short-Term Memory, Residual Network, Neural Network	`inDefinedTermSet`

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