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add sections on rnn, lstm, gru, vae, etc used before transformers
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If we try to render the course to preview how our added content looks like, it throws the following error
```bash
sarthak@kde:~/Desktop/computer-vision-course$ doc-builder preview computer-vision-co…
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> Autoencoders provide a powerful framework for learning compressed representations
by encoding all of the information needed to reconstruct a data point in
a latent code. In some cases, autoencoder…
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This slide is very vague:
t03_features.pdf
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beta-VAE is also very good ref : http://openreview.net/forum?id=Sy2fzU9gl
Learning an interpretable factorised representation of the independent data gen- erative factors of the world without super…
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For the autoencoder in pyod, how do I adjust the learning rate?
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### Metadata
- Authors: Christopher P. Burgess, Irina Higgins, +4 authors Alexander Lerchner
- Organization: DeepMind
- Publish Date: 2018.04
- Paper: https://arxiv.org/pdf/1804.03599.pdf
- 3rd-p…
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Hi,
I was going to work on exercise 9 from Chapter 17 (denoising autoencoder), and wanted to try using the best classifier I had trained so far on MNIST digits which is an SE-ResNET, as a basis for…
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### Description
To use different quantum computing techniques focused on Machine Learning, as a principal base for the quantum autoencoder to be able to reduce data in a medical dataset, also to …