andy
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Affected files: .obsidian/graph.json .obsidian/workspace-mobile.json .obsidian/workspace.json STEM/AI/Ethics.md STEM/AI/Neural Networks/Activation Functions.md STEM/AI/Neural Networks/CNN/CNN.md STEM/AI/Neural Networks/Deep Learning.md STEM/AI/Neural Networks/MLP/Back-Propagation.md STEM/AI/Neural Networks/MLP/MLP.md STEM/AI/Neural Networks/Neural Networks.md STEM/AI/Neural Networks/Properties+Capabilities.md STEM/AI/Neural Networks/RNN/LSTM.md STEM/AI/Neural Networks/RNN/RNN.md STEM/AI/Neural Networks/RNN/VQA.md STEM/AI/Neural Networks/SLP/SLP.md STEM/AI/Neural Networks/Training.md STEM/AI/Neural Networks/Transformers/Attention.md STEM/AI/Neural Networks/Transformers/LLM.md STEM/AI/Neural Networks/Transformers/Transformers.md STEM/Signal Proc/System Classes.md STEM/img/back-prop-equations.png STEM/img/back-prop-weight-changes.png STEM/img/back-prop1.png STEM/img/back-prop2.png STEM/img/cnn+lstm.png STEM/img/deep-digit-classification.png STEM/img/deep-loss-function.png STEM/img/llm-family-tree.png STEM/img/lstm-slp.png STEM/img/lstm.png STEM/img/matrix-dot-product.png STEM/img/ml-dl.png STEM/img/photo-tensor.png STEM/img/relu.png STEM/img/rnn-input.png STEM/img/rnn-recurrence.png STEM/img/slp-arch.png STEM/img/threshold-activation.png STEM/img/transformer-arch.png STEM/img/vqa-block.png
22 lines
787 B
Markdown
22 lines
787 B
Markdown
- Feed-forward
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- Single hidden layer can learn any function
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- Universal approximation theorem
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- Each hidden layer can operate as a different feature extraction layer
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- Lots of weights to learn
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- [[Back-Propagation]] is supervised
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![[mlp-arch.png]]
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# Universal Approximation Theory
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A finite feed-forward MLP with 1 hidden layer can in theory approximate any mathematical function
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- In practice not trainable with [[Back-Propagation|BP]]
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![[activation-function.png]]
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![[mlp-arch-diagram.png]]
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## Weight Matrix
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- Use matrix multiplication for layer output
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- TLU is hard limiter
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![[tlu.png]]
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- $o_1$ to $o_4$ must all be one to overcome -3.5 bias and force output to 1
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![[mlp-non-linear-decision.png]]
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- Can generate a non-linear [[Decision Boundary|decision boundary]] |