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Recurrent Neural Networks (RNN)
hard

What is the correct sequence of operations when applying an RNN to model a sequence of data?

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Choose AnswerChoose the Best Answer

A

Input data → Generate hidden state → Output prediction

B

Generate hidden state → Input data → Output prediction

C

Output prediction → Input data → Generate hidden state

D

Input data → Output prediction → Generate hidden state

Understanding the Answer

Let's break down why this is correct

An RNN reads the sequence one piece at a time. Other options are incorrect because It sounds like the RNN could know something before seeing any data, but it cannot; The prediction cannot come before any data.

Key Concepts

Recurrent Neural Networks
Sequence Modeling
Hidden States
Topic

Recurrent Neural Networks (RNN)

Difficulty

hard level question

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Definition
Definition

Recurrent neural networks, including LSTM and gated recurrent networks, have been widely used for sequence modeling and transduction tasks. These networks factor computation along symbol positions and generate hidden states sequentially, limiting parallelization and efficiency.

Topic Definition

Recurrent neural networks, including LSTM and gated recurrent networks, have been widely used for sequence modeling and transduction tasks. These networks factor computation along symbol positions and generate hidden states sequentially, limiting parallelization and efficiency.

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