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Statistical Deep Learning

The course treats basic as well as modern concepts of statistical learning in terms of artificial neural networks (deep learning), with applications in statistical data analysis.

Topics treated include feedforward networks, regularization and optimization of networks with many layers, convolutional networks, recurrent networks and validation methods. In addition, mathematical interpretations of networks are given, such as nonlinear regression with different link functions for the outcome variable. The course includes some of the following topics; autoencoders, representation learning, deep generative methods, and information theoretic concepts of deep learning.

Overlapping courses

The material in this course is also covered in part in the course Machine Learning (DA7063), and they should not be included in the same degree if the degree also contains Statistical Learning (MT7038).

This course also overlaps with Djupinlärning i Data Science (DA7064) and they should not be included in the same degree.

DA7063 and DA7064 were given for the last time in the spring 2022.