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About CS7015 (Deep Learning) : Lecture 7
The document discusses autoencoders, including: 1) Autoencoders are neural networks that encode an input into a hidden representation and then decode the hidden representation to reconstruct the input. 2) Undercomplete autoencoders have fewer hidden units than inputs and learn a compressed representation, similar to PCA. Overcomplete autoencoders can learn identity encodings. 3) Autoencoders are trained to minimize a reconstruction error loss between inputs and outputs using backpropagation.
Detailed Information
| Author: | ['Mohd Saud'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 55 |
| Language: | English |
| Format: | |
| Price: | FREE |
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