Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of large-scale annotated datasets and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which were previously addressed with hand-crafted features.

Architectures such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) or the Transformer based on Attention mechanisms have shaped a brand new scenario in signal processing. This course will cover the basic principles of deep learning from both an algorithmic and computational perspectives.

The course webpage can be found: [2020], [2019], [2018]

DLAI Lectures (2020)