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Current topics in Materials Science: Machine Learning
Fridays 3. DS (11:10-12:40) in HAL 115, Hallwachsstraße 3
Start: !!! 19.10.2018 !!!
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| 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 |
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last modified: 2020.12.01 Tue
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Prof. Dr. Gianaurelio Cuniberti
secretariat:
postal address:
Institute for Materials Science
TU Dresden
01062 Dresden, Germany
visitors and courier address:
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