This online course, to be held over one half-day, will teach participants how deep learning/neural networks work, and how they may be applied in practice by using either Python or R programming.
The audience for this course is PhD students, post-docs, and researchers at the University of Lausanne (UNIL) who would like to use machine learning methods in their research.
At the end of the course, the participants should be able to understand how the machine learning (neural network) algorithm works, run a simple machine learning code in Python or R, and be able to choose properly the hyper-parameters of the model.
Prior basic knowledge of statistics, including simple linear algebra techniques such as vectors, matrices and matrix multiplication, are required, as is familiarity with either Python or R programming. Participants must also have an account on the UNIL clusters.