Machine learning school for beginners and intermediates
This course is designed to be a gateway, allowing someone who knows how to code to get into machine learning. We will give a brief overview of most modern and traditional machine learning techniques, with a neutron or muon based application wherever possible. The school will run Feburary 15th - 19th 2021 (inclusive) and will consist of two lectures per day, each paired with a corresponding tutorial where you can implement the technique you have just learnt.
Requisites:
Basic skills in Python, including numpy/scipy/similar, Matlab also possible but all lectures will be in Python.
Aims:
·
Remove the mystery surrounding machine learning for people wanting to try it for themselves.
·
Share hints and tips between people with some experience
·
Illustrate examples of problems that can be solved with one or the other type of neural networks.
·
Bridge the gap between the domain scientists and AI experts.
Applications for ISIS participants now closed. For other institutions please refer to your contact for instructions on how to apply.
All other institutions please apply following instructions from your local school representitive.
Lecturers and and School Support:
Anders Kaestner PSI
Andrew McCluskey ESS
Emmanouela Rantsiou PSI
Gagik Vardanyan ILL
Guanghan Song ILL
James Durant ISIS
Jeyan Thiyagalingam SciML
Jos Cooper ISIS
Keith Butler SciML
Kuangdai Leng SciML
Marina Ganeva MLZ
Mario Teixeira Parente MLZ
Paul Baumeister JSC