DCSR, A Gentle Introduction to Deep Learning with Python and R

Machine learning methods are nowadays used in a wide variety of applications such as image and text classification, and weather forecasting. In this course, you will learn how a very popular method, namely Deep Learning (or Neural Network), works and may be applied in practice by using either Python or R programming.

Objectives		Acquire the key competencies that are needed to apply deep learning methods to simple datasets.
Target audience		Any PhD students, post-docs, researchers of UNIL who would like to use deep learning methods in their research.
Content		At the end of the course, the participants are expected to: Understand how the deep learning (neural network) algorithm works. Run a simple machine learning code in Python or R. Be able to choose properly the hyper-parameters of the model.
Length		1 half-day
Organization		Every 6 months.
Location		To be defined or remotely
Prerequisites		Basic knowledge of statistics, including simple linear algebra techniques such as vectors, matrices and matrix multiplication. Be confortable with either Python or R programming. Have an account on the UNIL clusters.

IMPORTANT: Please register using your Unil email address!

Course dates and registration