From 15 to 19 February, I was part of a series of online lectures at the LENS ISIS Machine Learning school. It was prepared in collaboration with scientists from neutron facilities (ESS, ILL, ISIS, PSI) other than MLZ at Garching.
We had around 60 interested participants from the mentioned facilities each day. Our aim was to give an understandable overview over the area of machine learning (ML) and its basic subareas to neutron scientists who are generally interested and/or think about applying ML techniques to their problems.
Each lecture was split into a formal talk and a short hands-on tutorial session. I will provide a link to the recordings of the talks and tutorial material once they are available. A curriculum of the school can be found at the end of this post.
I want to thank all the other organizers for their engagement in making this school possible and hope to meet them in person someday.
- Lecture 1: Introduction to deep learning and neural networks
- Lecture 2: Dense neural networks and regression
- Lecture 3: Convolutional neural networks and classification
- Lecture 4: Traditional ML methods
- Lecture 5: Image segmentation
- Lecture 6: Recurrent neural networks
- Lecture 7: Generative Adversarial Networks, GANs
- Lecture 8: Natural language processing and speech recognition
- Lecture 9: Uncertainty and attention
- Lecture 10: Unsupervised and reinforcement learning