Current topics in Materials Science: Machine Learning

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

title:	Current topics in Materials Science: Machine Learning
uni code:
type of lectures:	Modulvorlesung
given by:	G. Cuniberti , T. Lehmann
lecturer:	G. Cuniberti
schedule:	2018WS Fridays 3. DS (11:10-12:40)
course language:	English
room:	HAL 115, Hallwachsstraße 3
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

last modified: 2019.03.20 Mi

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