Deep Learning

Notes on optimization, neural-network architectures, recurrent layers, transformers, convolutional networks, and generative models.

• Training foundations

  Gradient descent · Weight initialization

• Sequence models

  Recurrent layers · Transformers

• Vision

  Convolutional neural networks

• Generative models

  GANs · Autoencoders

• Code

  Browse worked implementations →