Autoencoders

I was given a presentation on autoencoders and how they work at tfug hyd webinar.

Transcript

1. Autoencoders
2. What is an autoencoder
3. Important Properties 1. Data-specific 2. Lossy 3. Unsupervised
4. Encoder
5. Latent vector
6. Decoder
7. Autoencoder
8. Loss function
9. Autoencoders with TF Encoder
10. Autoencoders with TF Decoder
11. Autoencoders with TF Training
12. Applications of Autoencoders Image Reconstruction
13. Applications of Autoencoders Dimensionality reduction
14. Applications of Autoencoders Denoising data
15. Applications of Autoencoders Image colorization
16. Applications of Autoencoders Image/data generation
17. Applications of Autoencoders • Sequence to sequence prediction ◦ predict the next frame of a video ◦ generate fake videos • Recommendation system • Feature Extraction • Image Compression • latent space clustering
18. 1. Sparse Autoencoder 2. Autoencoder 3. Convolutional Autoencoder 4. Denoising 5. Sequence-to-sequence Autoencoder 6. Variational Autoencoder Types of Autoencoders
19. Any Questions??
20. Udaykiran.dev