Carlos Teijeiro Barjas (SURFsara), Haukur-Páll Jónsson (SURFsara)
(to be confirmed)
Deep learning has become a really hot topic for different areas of research in order to extract information and correlations between huge amounts of data that are otherwise very difficult or even effectively impossible to process in a purely analytic way. This workshop will begin with a morning session that will be presenting an overview of machine learning techniques, and later on introducing the basics concepts needed to understand artificial neural networks.
The afternoon session will be eminently practical and applied to life sciences. You may be able to learn the basic use of tools for image processing and tune the results of your neural network to achieve your goals.
The hands-on exercises will be performed using the Python programming language in a Jupyter notebook.
The course is aimed at graduate students and other researchers, particularly from life sciences, who would like to know how the different deep learning techniques can be applied to their everyday work.
No other experience is strictly necessary, but some affinity with general programming or scripting may be useful.
SURF Utrecht. Kantoren Hoog Overborch (Hoog Catharijne), Moreelsepark 48, room 3.5, 3511 EP Utrecht.
Get directions with
This workshop is sponsored and supported by ELIXIR-EXCELERATE. ELIXIR-EXCELERATE is funded by the European Commission within the Research Infrastructures programme of Horizon 2020, grant agreement number 676559.
During this workshop you will be granted access to the computing facilities of SURFsara.
In order to use them, you will need an up-to-date web browser in your own laptop. Additionally,
it is highly recommended that your laptop has access to the software described below.
The Bash Shell
Bash is a commonly-used shell that gives you the power to do simple
tasks more quickly.
Click on "Next" four times (two times if you've previously
installed Git). You don't need to change anything
in the Information, location, components, and start menu screens.
Select “Use the nano editor by default” and click on “Next”.
Keep "Use Git from the Windows Command Prompt" selected and click on "Next".
If you forgot to do this programs that you need for the workshop will not work properly.
If this happens rerun the installer and select the appropriate option.
Click on "Next".
Keep "Checkout Windows-style, commit Unix-style line endings" selected and click on "Next".
Select "Use Windows' default console window" and click on "Next".
Click on "Install".
Click on "Finish".
If your "HOME" environment variable is not set (or you don't know what this is):
Open command prompt (Open Start Menu then type cmd and press [Enter])
Type the following line into the command prompt window exactly as shown:
setx HOME "%USERPROFILE%"
Press [Enter], you should see SUCCESS: Specified value was saved.
Quit command prompt by typing exit then pressing [Enter]
This will provide you with both Git and Bash in the Git Bash program.
The default shell in all versions of macOS is Bash, so no
need to install anything. You access Bash from the Terminal
See the Git installation video tutorial
for an example on how to open the Terminal.
You may want to keep
Terminal in your dock for this workshop.
The default shell is usually Bash, but if your
machine is set up differently you can run it by opening a
terminal and typing bash. There is no need to
When you're writing code, it's nice to have a text editor that is
optimized for writing code, with features like automatic
color-coding of key words. The default text editor on macOS and
Linux is usually set to Vim, which is not famous for being
intuitive. If you accidentally find yourself stuck in it, hit
the Esc key, followed by :+Q+!
(colon, lower-case 'q', exclamation mark), then hitting Return to
return to the shell.
Python is a popular language for
research computing, and great for general-purpose programming as
well. Installing all of its research packages individually can be
a bit difficult, so we recommend
an all-in-one installer.
Regardless of how you choose to install it,
please make sure you install Python version 3.x
(e.g., 3.6 is fine).
We will be running Python code using the Jupyter notebook,
a programming environment that runs in a web browser. For this to work you will need a reasonably
up-to-date browser. The current versions of the Chrome, Safari and
Firefox browsers are all
(some older browsers, including Internet Explorer version 9
and below, are not).
Download the Python 3 installer for Linux.
(The installation requires using the shell. If you aren't
comfortable doing the installation yourself
stop here and request help at the workshop.)
Open a terminal window.
and then press
Tab. The name of the file you just downloaded should
appear. If it does not, navigate to the folder where you
downloaded the file, for example with:
Then, try again.
Press Return. You will follow the text-only prompts. To move through
the text, press Spacebar. Type yes and
press enter to approve the license. Press enter to approve the
default location for the files. Type yes and
press enter to prepend Anaconda to your PATH
(this makes the Anaconda distribution the default Python).