Advanced course in Computational Physics, see texbook at http://compphysics.github.io/ComputationalPhysics2/doc/LectureNotes/_build/html/ with an emphasis on computational quantum mechanics, machine learning and quantum computing.

Course on Machine Learning and Statistical data Analysis with book at https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/intro.html. Contains Linear and Logistic Regression, Neural Networks and Deep Learning methods, Decision Trees, Random forests, Boosting methods and other ensemble methods, support vector machines and central unsupervised learning algorithms.

Material on Machine Learning methods applied to Physics analysis, with an emphasis on Regression and Deep Learning Methods. https://compphysics.github.io/MLSummerSchool/doc/web/course.html gives you direct access to the learning material with lectures slides and jupyter notebooks.

This site contains all document relevant for the Machine Learning courses of the Erasmus+ network. Jupyter-book link at https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/intro.html.

course design documents for computational and numerical methods in physics

This site contains all document relevant for the Machine Learning courses of the Erasmus+ network. Jupyter-book link at https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/intro.html.