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10:53
YouTube
CodeEmporium
Autoencoders - EXPLAINED
Data around us, like images and documents, are very high dimensional. Autoencoders can learn a simpler representation of it. This representation can be used in many ways: - fast data transfers across a network - Self driving cars (Semantic Segmentation) - Neural Inpainting: Completing sections of an image, or removing watermarks - Latent ...
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AI • Machine Learning • Tech on Instagram: "A variational autoencoder (VAE) is a generative model that learns to represent data not as fixed points, but as probability distributions in a hidden space. Like other neural networks, it uses large matrices with tunable parameters to process the input, but instead of producing a single compressed vector, it outputs a mean and variance that define a distribution the input could come from. During training, the model samples from this distribution and tr
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