Deep Learning for Multimedia

This course introduces the deep learning methods that underpin modern multimedia processing, covering images, video, and sequential data. Starting from the foundations of neural network learning, it progressively builds towards the architectures that dominate the field today, including convolutional networks, recurrent models, generative models, and transformers, with a consistent focus on multimedia applications such as visual recognition, content generation, and compression.