Introduction to Deep Learning 2022

Deep learning based approaches outperform traditional approaches in a number of applications spanning from data analysis  to image processing and natural language processing. The availability of large sets of annotated data, powerful yet affordable parallel computers and improved optimization techniques are behind this revolution. This course will provide first an introduction to multilayer neural networks and its cornerstones such as learning with descent of the backpropagated error gradient. Next, convolutional and deep architectures will be introduced in the context of image processing, Finally, the course will look into recurrent architectures for time series and natural language processing.