Autoencoders

Summary

Networks trained to compress input into a smaller representation and reconstruct it — used for dimensionality reduction, denoising, and as a building block for generative models.

How to Learn This

1Build a simple autoencoder for image reconstruction or dimensionality reduction.
2Learn the difference between a standard autoencoder and a variational autoencoder (VAE).
3Use the learned latent space to visualize how the model compresses data.

Transfer Learning

Generative Adversarial Networks (GANs, Overview)

More topics in Deep Learning Architectures

Convolutional Neural Networks (CNNs)Pooling Layers Recurrent Neural Networks (RNNs)LSTMs & GRUs Sequence-to-Sequence Models Attention Mechanism Transformer Architecture Positional Encoding Transfer Learning Generative Adversarial Networks (GANs, Overview)

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