PRONIA Machine Learning Autumn School
There will be daily seminars and semi-structure tutorials with specific teaching aims on each day. On the last day, the participants will form teams using their knowledge of machine learning methods in NeuroMiner and compete to see who can create the most predictive models for a new dataset. At the end of the autumn school we hope that everyone will be more confident and connected to facilitate some great translational science in PRONIA.
During the school, we have planned some interesting lessons that will build your knowledge from basic data entry on the first day to advanced techniques on the penultimate day. This will be facilitated through daily seminars and then semi-structured tutorials with specific teaching aims and utilising the same test dataset. There will also be multiple social events in order for everyone to meet each other, learn from one another, and potentially form longer-term collaborations.
Recommendations for the course
To get the most out of the autumn school, we strongly recommend that you learn about machine learning, basic MATLAB operations, and NeuroMiner prior to the course. More information in this respect will be published here in due time.
Hardware and Software Requirements for the course
It is a requirement that you have a laptop computer with at least 2GB of RAM running Windows/Linux/Mac with MATLAB2014b or above. Please note that NeuroMiner will not work with earlier versions of MATLAB. It's also a requirement that you have downloaded NeuroMiner and SPM by following the directions in the manual. We recommend the WFU Pickatlas toolbox for SPM, the MATLAB Statistics and Optimization Toolbox in order to use advanced training options in the matLearn toolbox, and the MATLAB Statistics and Machine Learning Toolbox for imputation functions. Please check that NeuroMiner is loading correctly by following the directions in the manual.