Aims
The course aims at two aspects of machine learning.
The first goal is an introduction to statistical mechanics of learning, which aims at describing the typical learning behavior of neural networks, discussion of the generalization performance of strongly overparametrized neural networks. Information field theoretic description of ultrawide neural networks. The second aim is to give an introduction to machine learning techniques and its applications in natural sciences. It will include fields of image recognition, time series analysis and reinforcement learning with examples and applications of neural networks in fluid mechanics.
Continue reading “[BuildMoNa] ATM: Deep Learning/Machine Learning (September 16-17, 2021)”