Machine learning (ML) methods are used for a wide variety of problems from identifying cats in images to automatic text translation and speech recognition. Formally hard problems of AI have been solved by modern implementations of deep learning and the new methods are also increasingly applied to many fields of science.
In this introductory seminar we want to explore the possibilities of ML techniques in general and its usages in the neurosciences in particular.
With a focus on practical programming training we will implement basic ML algorithms that can be used in the field. We will use previously recorded electrophysical data, databases from public sources and you are also encouraged to bring your own data to test the algorithms on.
You will learn to use various data sources, like Kaggle to obtain rich data sets. Basic visualization techniques in Matlab will be trained and what to look out for in datasets. You will learn to implement basic ML algorithms and how to use available Matlab methods for ML. A large focus will be to use state-of-the-art techniques like Deep Learning to solve problems in the neurosciences.

Discuss your Matlab questions with other neuroscientists. For PhD students and postdocs of SFB 874 and IGSN

Introduction to Matlab for PhD students of SFB 874 and IGSN