Abstract: In this seminar we will present recent applications of deep learning methods to nuclear physics, with selected examples from the analysis of experimental data to nuclear many-body problems. The aim is to show the potential of deep learning methods to a broad range of nuclear physics research topics. We will also present a general class of machine learning algorithms called parametric matrix models. We will show some selected examples of applications of parametric matrix models to a series of different challenges that show their performance for a wide range of problems.