Deep Learning Course (NYU, Spring 2020) - Week 7 – Practicum: Under- and over-complete autoencoders

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What you'll learn

This course includes

42.5 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

Deep Learning Yann LeCun autoencoder denoising autoencoder contractive autoencoder under-complete over-complete inpainting generative restoration PyTorch

Full Transcript

Course website: http://bit.ly/DLSP20-web Playlist: http://bit.ly/pDL-YouTube Speaker: Alfredo Canziani Week 7: http://bit.ly/DLSP20-07 0:00:00 – Week 7 – Practicum PRACTICUM: http://bit.ly/DLSP20-07-3 We discussed some applications of Autoencoders and talked about why we want to use them. Then we talked about different architectures of Autoencoders (under or over complete hidden layer), how to avoid overfitting issues and the loss functions we should use. Finally, we implemented a standard Autoencoder and a denoising Autoencoder. 0:00:55 – Application of Autoencoders 0:14:39 – Architecture and loss function in Autoencoders 0:41:31 – Notebook example for different types of Autoencoders

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