Vorlesung Ankündigung 2018WS

Current topics in Materials Science: Machine Learning ( )

2018WS, Fridays 3. DS (11:10-12:40) in HAL 115, Hallwachsstraße 3

  Start: !!! 19.10.2018 !!!

lecturer:G. Cuniberti
credits:Students of Materials Science, Nanobiophysics, Molecular Bioengineering, Organic and Molecular Electronics, Nanoelectronic Systems, Physics, Chemistry, Electrical Engineering, Computer Science, etc.; PhD students
summary:We offer a hands-on approach to machine learning and data science as well as its prospective use in materials science. We discuss the application of machine learning methods like Random Forests, Gradient Boosting, support vector machines and neural networks, including data preparation, model selection and evaluation. Apart from the theoretical discussion of those concepts, we will start to implement them in Python. The course is complemented by student presentations of publications on data-driven materials science.
Prerequisites: Familiarity with Python programming
url:for ToC, literature, questions, comments etc. please visit the web site given below.