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Overview
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This course explains autoencoders intuitively, covering encoders, decoders, training, compression, deep and convolutional architectures, and latent spaces. It also introduces applications including data generation, denoising, and anomaly detection.
Syllabus
Intro
Key idea in autoencoders
Encoder
PCA vs Encoders
Decoder
Training autoencoders
Optimal autoencoder
Deep Autoencoder
Deep Convolutional Autoencoder
What's the point of compression/decompression?
Autoencoder applications
Generation with autoencoders
Denoising with autoencoders
Anomaly detection with autoencoders
Coming next
Taught by
Valerio Velardo - The Sound of AI