stem/AI/Neural Networks/Architectures.md
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STEM/AI/Neural Networks/Architectures.md
STEM/AI/Neural Networks/CNN/CNN.md
STEM/AI/Neural Networks/CNN/Examples.md
STEM/AI/Neural Networks/CNN/FCN/FCN.md
STEM/AI/Neural Networks/CNN/GAN/DC-GAN.md
STEM/AI/Neural Networks/CNN/GAN/GAN.md
STEM/AI/Neural Networks/CNN/Interpretation.md
STEM/AI/Neural Networks/Deep Learning.md
STEM/AI/Neural Networks/MLP/MLP.md
STEM/AI/Neural Networks/SLP/Least Mean Square.md
STEM/AI/Neural Networks/Transformers/Attention.md
STEM/AI/Neural Networks/Transformers/Transformers.md
STEM/img/feedforward.png
STEM/img/multilayerfeedforward.png
STEM/img/recurrent.png
STEM/img/recurrentwithhn.png
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Markdown

# Single-Layer Feedforward
- *Acyclic*
- Count output layer, no computation at input
![[feedforward.png]]
# Multilayer Feedforward
- Hidden layers
- Extract higher-order statistics
- Global perspective
- Helpful with large input layer
- Fully connected
- Every neuron is connected to every neuron adjacent layers
- Below is a 10-4-2 network
![[multilayerfeedforward.png]]
# Recurrent
- At least one feedback loop
- Below has no self-feedback
![[recurrent.png]]
![[recurrentwithhn.png]]
- Above has hidden neurons