Learning Path
Question & Answer
Choose the Best Answer
hidden states
input sequences
activation functions
output layers
Understanding the Answer
Let's break down why this is correct
The hidden state is produced one step after another. Other options are incorrect because Input sequences are the data that the network reads, but they do not force the model to wait; Activation functions add non‑linearity, but they are applied at each step and do not create a chain of dependencies.
Key Concepts
Recurrent Neural Networks (RNN)
medium level question
understand
Deep Dive: Recurrent Neural Networks (RNN)
Master the fundamentals
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.
Ready to Master More Topics?
Join thousands of students using Seekh's interactive learning platform to excel in their studies with personalized practice and detailed explanations.