Research - 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 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
Once per year
Location
In presential
Practicals
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
IMPORTANT: To do the practicals
- On UNIL JupyterLab: You need to be able to access the eduroam wifi with your UNIL account or via the UNIL VPN
- On your laptop: No account requirement
- On Curnagl: Please register using your UNIL email address
- Note that in all cases you need to bring your own laptop