# 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 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 hyperparameters 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