In this series of lectures, we'll cover at the main models used in deep learning, seen from both analytical and generative AI perspectives.
After reviewing the historical models, we'll look at convolutional and recurrent networks, before moving on to more recent architectures such as transformers and the main generative models for images and texts.
The courses will combine theoretical approaches with practical illustrations.