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What you, as student, need to do before the course starts

setup Setting up your system for the course

You need to have done the following setup on your laptop before the course starts. Given the prerequisites, you should typically be fine doing this by yourself, but if you run into unexpected problems, we will have a drop-in help session on Friday 17/3 2023, from 10AM to 12PM, zoom link here Links to an external site.. If you discover errors below, please let us know.

NB! If you don't have the permissions to install software on your laptop, you must ask your system administrator to either give you such premissions or install the software for you. This will require extra time so please plan for this!

terminal Terminal setup

  • Unix, Linux and MacOSX already have a terminal app installed:
    • on MacOSX, you can find it by searching for "Terminal" in the launch pad.
  • On Windows, you may use, e.g., PowerShell, cmd

Conda setup

1. Download and install Conda and Mamba

If you have Linux or MacOSX, you will simply install conda. If you have Windows, there are a few extra steps to complete before you can install conda, see below.

We suggest installing Miniconda3 and not Anaconda.

On Mac OS X

First, make sure you have Xcode and CommandLineTools installed and updated to latest version (in AppStore). If you have not already installed CommadLineTools, go to a terminal window and run:

  xcode-select --install

First download the latest version of Miniconda3 and run it to install.

  curl -o Miniconda3-latest-MacOSX-x86_64.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
  sh Miniconda3-latest-MacOSX-x86_64.sh

Follow the instructions on screen, scrolling down, pressing ENTER and replying yes when necessary. Install it in the default directory. Restart your terminal window to apply modifications. After restarting, you can type the command below to install Mamba:

  conda init
  conda install -n base -c conda-forge mamba
On Ubuntu

First download the latest version of Miniconda3 and run it to install.

  wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
  sh Miniconda3-latest-Linux-x86_64.sh

Follow the instructions on screen replying yes when necessary. Restart your terminal window to apply modifications. After restarting, you can type the command below to install Mamba:

  conda init
  conda install -n base -c conda-forge mamba
On Windows 10

Unfortunately, not all packages available on conda are compatible with windows machines. The good news is that Windows 10 offers native linux support via the Windows Subsystem for Linux (WSL2). This allows you to run linux/bash commands from within windows without the need of a virtual machine nor a dual-boot setup (i.e. having 2 operating systems). However, WSL does not offer a complete support for graphical interfaces (such as RStudio in our case), so we need additional steps to make that happen.

      1. On Windows 10, install the WSL if you don’t have it. Follow the instructions here: https://docs.microsoft.com/en-us/windows/wsl/install-win10 Links to an external site.

      2. Once you have that installed, you can download and install MobaXterm (which is the enhanced terminal with graphical capacity): https://mobaxterm.mobatek.net Links to an external site.
        It is recommended that you INSTALL the program and not use the portable version.

      3. Inside MobaXterm, you will probably will see that your WSL is already listed on the left panel as an available connection. Just double-click it and you will be accessing it via MobaXterm. If by any chance you don’t see it there, close MobaXterm and go to the WSL terminal, because probably the WSL is not allowing SSH connections. You can follow this link Links to an external site. for the instructions on how to do it. You need to complete until the step Start or restart the SSH service, while the further steps are optional, but might be useful.

      4. Inside MobaXterm, download Conda with the command:

  wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
      1. Inside MobaXterm, type the commands below to install Conda. Follow the instructions for the installation there.
  cd ~/Downloads
  sh Miniconda3-latest-Linux-x86_64.sh
      1. Inside MobaXterm, Follow the instructions on screen replying yes when necessary. Restart your terminal window to apply modifications. After restarting, you can type the command below to install Mamba:
  conda init
  conda install -n base -c conda-forge mamba
      1. Inside MobaXterm, type the commands below to install the X-server graphical packages that will be used to launch RStudio. https://docs.anaconda.com/anaconda/install/linux/ Links to an external site.
  sudo apt-get update
  sudo apt-get install libgl1-mesa-glx libegl1-mesa libxrandr2 libxrandr2 libxss1 libxcursor1 libxcomposite1 libasound2 libxi6 libxtst6
      1. Close and open all application and Inside MobaXterm, you will probably will see that your WSL is already listed on the left panel as an available connection. Just double-click it and you will be accessing it via MobaXterm.


2. Create a conda environment from file

To download the your_environment.yml file using the command on Terminal:

curl -o nn_dl_python.yaml https://raw.githubusercontent.com/NBISweden/workshop-neural-nets-and-deep-learning/master/common_assets/conda_envs/nn_dl_python.yaml

(or, alternatively, wget https://raw.githubusercontent.com/NBISweden/workshop-neural-nets-and-deep-learning/master/common_assets/conda_envs/nn_dl_python.yaml)

After this, you should have a file named nn_dl_python in your directory (it does not matter where). Next, type:

mamba env create -f nn_dl_python.yaml

Several messages will show up on your screen and will tell you about the installation process. This may take a few minutes depending on how many packages are to be installed.

##...
##Downloading and Extracting Packages
##cachetools-4.2.4     | 12 KB     | ############################################################################# | 100%
##pydot-1.4.2          | 43 KB     | ############################################################################# | 100%
##argcomplete-1.12.3   | 34 KB     | ############################################################################# | 100%
##...
##Preparing transaction: done
##Verifying transaction: done
##Executing transaction: done
##...
##done
#
# To activate this environment, use
#
#     $ conda activate nn_dl_python
#
# To deactivate an active environment, use
#
#     $ conda deactivate

3. Activate the environment

Once the environment is created, we need to activate it in order to use the softwares and packages inside it. To activate an environment type:

conda activate nn_dl_python

From this point on you can run any of the contents from the workshop. For instance,

You can test the environment by saving the first of the course's labs:

curl -LJ -o introduction_to_keras_1.ipynb https://github.com/NBISweden/workshop-neural-nets-and-deep-learning/raw/master/session_annBuildingBlocks/lab_keras/introduction_to_keras_1.ipynb

Next, you can directly launch Jupyter Notebooks by typing from the same directory:

jupyter-notebook

Jupyter should open in your browser. Then, you should be able to open the notebook saved in the previous step ("introduction_to_keras_1.ipynb") and run some of the code cells within. If you get errors at any step and you don't know why, join the drop-in session before the course to troubleshoot with the teachers (see above).

4. Deactivate the environment

After you’ve ran all your analyses, you can deactivate the environment by typing:

conda deactivate

Google Google account setup

 Refresh yourself on Statistics and ML

You should refresh your memory about basic Statistics and Machine Learning, including the following subjects (includes links to lecture notes from the NBIS course, Introduction to Biostatistics and Machine Learning Links to an external site.)

setup Python programming

During the course, you will learn to use the python module keras. However, to follow code in the lectures and exercises, you should familiarize/refresh yourself with basic Python syntax, maybe focusing on:

  • the overall Python coding syntax, esp. the role of indentations
  • how to print to screen
  • variables types, assignment to variables
  • lists, dictionaries, indexing and slicing
  • how to call functions
  • if-else clauses
  • for and while loops
  • how to import from library modules and call module functions
  • how to define your own functions

There are a plethora of Python tutorials accessible on the internet (you just have to google). We here give just a few suggestions and we suggest you pick out the pieces of interest in these: